From noreply at r-forge.r-project.org Sun Mar 1 04:40:13 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Sun, 1 Mar 2015 04:40:13 +0100 (CET) Subject: [Pomp-commits] r1118 - pkg/pomp pkg/pomp/inst/include pkg/pomp/src www/vignettes Message-ID: <20150301034013.BAD50183C1E@r-forge.r-project.org> Author: kingaa Date: 2015-03-01 04:40:12 +0100 (Sun, 01 Mar 2015) New Revision: 1118 Added: www/vignettes/ecology.csl Modified: pkg/pomp/DESCRIPTION pkg/pomp/inst/include/pomp.h pkg/pomp/src/pomp.h Log: - rearrange pomp.h Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-02-28 17:56:04 UTC (rev 1117) +++ pkg/pomp/DESCRIPTION 2015-03-01 03:40:12 UTC (rev 1118) @@ -1,8 +1,8 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.62-1 -Date: 2015-02-27 +Version: 0.62-2 +Date: 2015-02-28 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), person(given=c("Edward","L."),family="Ionides",role=c("aut")), Modified: pkg/pomp/inst/include/pomp.h =================================================================== --- pkg/pomp/inst/include/pomp.h 2015-02-28 17:56:04 UTC (rev 1117) +++ pkg/pomp/inst/include/pomp.h 2015-03-01 03:40:12 UTC (rev 1118) @@ -8,201 +8,9 @@ #include #include -// FACILITIES FOR EXTRACTING R OBJECTS FROM THE 'USERDATA' SLOT -const SEXP get_pomp_userdata (const char *name); -const int *get_pomp_userdata_int (const char *name); -const double *get_pomp_userdata_double (const char *name); - // FACILITY FOR EVALUATING A SET OF PERIODIC BSPLINE BASIS FUNCTIONS void periodic_bspline_basis_eval (double x, double period, int degree, int nbasis, double *y); -// PROTOTYPE FOR PARAMETER TRANSFORMATION FUNCTION. -typedef void pomp_transform_fn (double *pt, double *p, int *parindex); - -// PROTOTYPE FOR STOCHASTIC SIMULATION ALGORITHM REACTION-RATE FUNCTION, AS USED BY "GILLESPIE.SIM": -typedef double pomp_ssa_rate_fn(int j, double t, const double *x, const double *p, - int *stateindex, int *parindex, int *covindex, - int ncovar, double *covars); -// Description: -// on input: -// j = integer specifying the number of the reaction whose rate is desired -// t = time at which the rates are to be evaluated -// x = vector of state variables -// p = vector of parameters -// stateindex = pointer to vector of integers pointing to the states in 'x' in the order specified by -// the 'statenames' argument of 'SSA.simulator' -// parindex = pointer to vector of integers pointing to the parameters in 'p' in the order specified by -// the 'paramnames' argument of 'SSA.simulator' -// covindex = pointer to vector of integers pointing to the covariates in 'covars' in the order -// specified by the 'covarnames' argument of 'SSA.simulator' -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'SSA.simulator' -// returns the rate of the j-th reaction - -// PROTOTYPE FOR ONE-STEP SIMULATOR, AS USED BY "EULER.SIM" AND "ONESTEP.SIM": -typedef void pomp_onestep_sim(double *x, const double *p, - const int *stateindex, const int *parindex, const int *covindex, - int ncovars, const double *covars, - double t, double dt); -// Description: -// on input: -// x = pointer to state vector -// p = pointer to parameter vector -// stateindex = pointer to vector of integers pointing to the states in 'x' in the order specified by -// the 'statenames' argument of 'euler.simulator' -// parindex = pointer to vector of integers pointing to the parameters in 'p' in the order specified by -// the 'paramnames' argument of 'euler.simulator' -// covindex = pointer to vector of integers pointing to the covariates in 'covars' in the order -// specified by the 'covarnames' argument of 'euler.simulator' -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'euler.simulator' -// t = time at the beginning of the Euler step -// dt = size (duration) of the Euler step -// on output: -// x = contains the new state vector (i.e., at time t+dt) -// -// NB: There is no need to call GetRNGstate() or PutRNGstate() in the body of the user-defined function. -// The RNG is initialized before any call to this function, and the RNG state is written afterward. -// Inclusion of these calls in the user-defined function may result in significant slowdown. - - -// PROTOTYPE FOR ONE-STEP LOG PROBABILITY DENSITY FUNCTION, AS USED BY "ONESTEP.DENS": -typedef void pomp_onestep_pdf(double *f, - double *x1, double *x2, double t1, double t2, const double *p, - const int *stateindex, const int *parindex, const int *covindex, - int ncovars, const double *covars); -// Description: -// on input: -// x1 = pointer to state vector at time t1 -// x2 = pointer to state vector at time t2 -// t1 = time corresponding to x1 -// t2 = time corresponding to x2 -// p = pointer to parameter vector -// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by -// the 'statenames' argument of 'euler.density' -// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by -// the 'paramnames' argument of 'euler.density' -// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by -// the 'covarnames' argument of 'euler.density' -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'euler.density' -// on output: -// f = pointer to the probability density (a single scalar) - -// PROTOTYPE FOR DETERMINISTIC SKELETON EVALUATION -typedef void pomp_skeleton (double *f, double *x, double *p, - int *stateindex, int *parindex, int *covindex, - int ncovars, double *covars, double t); - -// Description: -// on input: -// x = pointer to state vector at time t -// p = pointer to parameter vector -// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by -// the 'statenames' slot -// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by -// the 'paramnames' slot -// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by -// the 'covarnames' slot -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'pomp.skeleton' -// t = time at the beginning of the Euler step -// on output: -// f = pointer to value of the map or vectorfield (a vector of the same length as 'x') - -// PROTOTYPE FOR MEASUREMENT MODEL SIMULATION -typedef void pomp_measure_model_simulator (double *y, double *x, double *p, - int *obsindex, int *stateindex, int *parindex, int *covindex, - int ncovars, double *covars, double t); -// Description: -// on input: -// x = pointer to state vector at time t -// p = pointer to parameter vector -// obsindex = pointer to vector of integers indexing the variables in 'y' in the order specified by -// the 'obsnames' slot -// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by -// the 'statenames' slot -// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by -// the 'paramnames' slot -// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by -// the 'covarnames' slot -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'pomp.skeleton' -// t = time at the beginning of the Euler step -// on output: -// y = pointer to vector containing simulated observations (length = nobs = nrow(data)) -// -// NB: There is no need to call GetRNGstate() or PutRNGstate() in the body of the user-defined function. -// The RNG is initialized before any call to this function, and the RNG state is written afterward. -// Inclusion of these calls in the user-defined function may result in significant slowdown. - - -// PROTOTYPE FOR MEASUREMENT MODEL DENSITY EVALUATOR -typedef void pomp_measure_model_density (double *lik, double *y, double *x, double *p, int give_log, - int *obsindex, int *stateindex, int *parindex, int *covindex, - int ncovars, double *covars, double t); -// Description: -// on input: -// y = pointer to vector of observables at time t -// x = pointer to state vector at time t -// p = pointer to parameter vector -// give_log = should the log likelihood be returned? -// obsindex = pointer to vector of integers indexing the variables in 'y' in the order specified by -// the 'obsnames' slot -// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by -// the 'statenames' slot -// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by -// the 'paramnames' slot -// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by -// the 'covarnames' slot -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'pomp.skeleton' -// t = time at the beginning of the Euler step -// on output: -// lik = pointer to scalar containing (log) likelihood - -// PROTOTYPE FOR PRIOR SIMULATION -typedef void pomp_rprior (double *p, int *parindex); -// Description: -// on input: -// p = pointer to parameter vector -// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by -// the 'paramnames' slot -// on output: -// p = pointer to vector containing draws from the prior -// -// NB: There is no need to call GetRNGstate() or PutRNGstate() in the body of the user-defined function. -// The RNG is initialized before any call to this function, and the RNG state is written afterward. -// Inclusion of these calls in the user-defined function may result in significant slowdown. - -// PROTOTYPE FOR PRIOR DENSITY EVALUATION -typedef void pomp_dprior (double *lik, double *p, int give_log, int *parindex); -// Description: -// on input: -// p = pointer to parameter vector -// give_log = should the log likelihood be returned? -// parindex = pointer to vector of integers indexing the parameters -// in 'p' in the order specified by the 'paramnames' slot -// on output: -// lik = pointer to vector containing likelihoods - -// UTILITY FOR EXPONENTIAL/GEOMETRIC RATE CONVERSION -// This function computes r such that if -// N ~ geometric(prob=1-exp(-r dt)) and T ~ exponential(rate=R), -// then E[N dt] = E[T] -// i.e., the rate r for an Euler process that gives the same -// expected waiting time as the exponential process it approximates. -// In particular r -> R as dt -> 0. -static R_INLINE double exp2geom_rate_correction (double R, double dt) { - return (dt > 0) ? log(1.0+R*dt)/dt : R; -} - // UTILITY FOR GAMMA WHITENOISE // This function draws a random increment of a gamma whitenoise process. // This will have expectation=dt and variance=(sigma^2*dt) @@ -379,6 +187,17 @@ for (i = 0; i < n; i++) xt[i] /= sum; } +// UTILITY FOR EXPONENTIAL/GEOMETRIC RATE CONVERSION +// This function computes r such that if +// N ~ geometric(prob=1-exp(-r dt)) and T ~ exponential(rate=R), +// then E[N dt] = E[T] +// i.e., the rate r for an Euler process that gives the same +// expected waiting time as the exponential process it approximates. +// In particular r -> R as dt -> 0. +static R_INLINE double exp2geom_rate_correction (double R, double dt) { + return (dt > 0) ? log(1.0+R*dt)/dt : R; +} + static R_INLINE double rbetabinom (double size, double prob, double theta) { return rbinom(size,rbeta(prob*theta,(1.0-prob)*theta)); } @@ -405,4 +224,188 @@ return (give_log) ? f : exp(f); } +// FACILITIES FOR EXTRACTING R OBJECTS FROM THE 'USERDATA' SLOT +const SEXP get_pomp_userdata (const char *name); +const int *get_pomp_userdata_int (const char *name); +const double *get_pomp_userdata_double (const char *name); + +// THE FOLLOWING ARE C PROTOTYPES FOR COMPONENTS OF POMP MODELS. +// THEY CANNOT BE USED WITHIN C SNIPPETS. + +// prototype for stochastic simulation algorithm reaction-rate function, as used by "gillespie.sim": +typedef double pomp_ssa_rate_fn(int j, double t, const double *x, const double *p, + int *stateindex, int *parindex, int *covindex, + int ncovar, double *covars); +// Description: +// on input: +// j = integer specifying the number of the reaction whose rate is desired +// t = time at which the rates are to be evaluated +// x = vector of state variables +// p = vector of parameters +// stateindex = pointer to vector of integers pointing to the states in 'x' in the order specified by +// the 'statenames' argument of 'SSA.simulator' +// parindex = pointer to vector of integers pointing to the parameters in 'p' in the order specified by +// the 'paramnames' argument of 'SSA.simulator' +// covindex = pointer to vector of integers pointing to the covariates in 'covars' in the order +// specified by the 'covarnames' argument of 'SSA.simulator' +// ncovars = number of covariates +// covars = pointer to a vector containing the values of the covariates at time t, as interpolated +// from the covariate table supplied to 'SSA.simulator' +// returns the rate of the j-th reaction + +// prototype for one-step simulator, as used by "euler.sim" and "onestep.sim": +typedef void pomp_onestep_sim(double *x, const double *p, + const int *stateindex, const int *parindex, const int *covindex, + int ncovars, const double *covars, + double t, double dt); +// Description: +// on input: +// x = pointer to state vector +// p = pointer to parameter vector +// stateindex = pointer to vector of integers pointing to the states in 'x' in the order specified by +// the 'statenames' argument of 'euler.simulator' +// parindex = pointer to vector of integers pointing to the parameters in 'p' in the order specified by +// the 'paramnames' argument of 'euler.simulator' +// covindex = pointer to vector of integers pointing to the covariates in 'covars' in the order +// specified by the 'covarnames' argument of 'euler.simulator' +// ncovars = number of covariates +// covars = pointer to a vector containing the values of the covariates at time t, as interpolated +// from the covariate table supplied to 'euler.simulator' +// t = time at the beginning of the Euler step +// dt = size (duration) of the Euler step +// on output: +// x = contains the new state vector (i.e., at time t+dt) +// +// NB: There is no need to call GetRNGstate() or PutRNGstate() in the body of the user-defined function. +// The RNG is initialized before any call to this function, and the RNG state is written afterward. +// Inclusion of these calls in the user-defined function may result in significant slowdown. + + +// PROTOTYPE FOR ONE-STEP LOG PROBABILITY DENSITY FUNCTION, AS USED BY "ONESTEP.DENS": +typedef void pomp_onestep_pdf(double *f, + double *x1, double *x2, double t1, double t2, const double *p, + const int *stateindex, const int *parindex, const int *covindex, + int ncovars, const double *covars); +// Description: +// on input: +// x1 = pointer to state vector at time t1 +// x2 = pointer to state vector at time t2 +// t1 = time corresponding to x1 +// t2 = time corresponding to x2 +// p = pointer to parameter vector +// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by +// the 'statenames' argument of 'euler.density' +// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by +// the 'paramnames' argument of 'euler.density' +// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by +// the 'covarnames' argument of 'euler.density' +// ncovars = number of covariates +// covars = pointer to a vector containing the values of the covariates at time t, as interpolated +// from the covariate table supplied to 'euler.density' +// on output: +// f = pointer to the probability density (a single scalar) + +// prototype for deterministic skeleton evaluation +typedef void pomp_skeleton (double *f, double *x, double *p, + int *stateindex, int *parindex, int *covindex, + int ncovars, double *covars, double t); + +// Description: +// on input: +// x = pointer to state vector at time t +// p = pointer to parameter vector +// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by +// the 'statenames' slot +// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by +// the 'paramnames' slot +// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by +// the 'covarnames' slot +// ncovars = number of covariates +// covars = pointer to a vector containing the values of the covariates at time t, as interpolated +// from the covariate table supplied to 'pomp.skeleton' +// t = time at the beginning of the Euler step +// on output: +// f = pointer to value of the map or vectorfield (a vector of the same length as 'x') + +// prototype for measurement model simulation +typedef void pomp_measure_model_simulator (double *y, double *x, double *p, + int *obsindex, int *stateindex, int *parindex, int *covindex, + int ncovars, double *covars, double t); +// Description: +// on input: +// x = pointer to state vector at time t +// p = pointer to parameter vector +// obsindex = pointer to vector of integers indexing the variables in 'y' in the order specified by +// the 'obsnames' slot +// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by +// the 'statenames' slot +// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by +// the 'paramnames' slot +// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by +// the 'covarnames' slot +// ncovars = number of covariates +// covars = pointer to a vector containing the values of the covariates at time t, as interpolated +// from the covariate table supplied to 'pomp.skeleton' +// t = time at the beginning of the Euler step +// on output: +// y = pointer to vector containing simulated observations (length = nobs = nrow(data)) +// +// NB: There is no need to call GetRNGstate() or PutRNGstate() in the body of the user-defined function. +// The RNG is initialized before any call to this function, and the RNG state is written afterward. +// Inclusion of these calls in the user-defined function may result in significant slowdown. + + +// prototype for measurement model density evaluator +typedef void pomp_measure_model_density (double *lik, double *y, double *x, double *p, int give_log, + int *obsindex, int *stateindex, int *parindex, int *covindex, + int ncovars, double *covars, double t); +// Description: +// on input: +// y = pointer to vector of observables at time t +// x = pointer to state vector at time t +// p = pointer to parameter vector +// give_log = should the log likelihood be returned? +// obsindex = pointer to vector of integers indexing the variables in 'y' in the order specified by +// the 'obsnames' slot +// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by +// the 'statenames' slot +// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by +// the 'paramnames' slot +// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by +// the 'covarnames' slot +// ncovars = number of covariates +// covars = pointer to a vector containing the values of the covariates at time t, as interpolated +// from the covariate table supplied to 'pomp.skeleton' +// t = time at the beginning of the Euler step +// on output: +// lik = pointer to scalar containing (log) likelihood + +// prototype for prior simulation +typedef void pomp_rprior (double *p, int *parindex); +// Description: +// on input: +// p = pointer to parameter vector +// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by +// the 'paramnames' slot +// on output: +// p = pointer to vector containing draws from the prior +// +// NB: There is no need to call GetRNGstate() or PutRNGstate() in the body of the user-defined function. +// The RNG is initialized before any call to this function, and the RNG state is written afterward. +// Inclusion of these calls in the user-defined function may result in significant slowdown. + +// prototype for prior density evaluation +typedef void pomp_dprior (double *lik, double *p, int give_log, int *parindex); +// Description: +// on input: +// p = pointer to parameter vector +// give_log = should the log likelihood be returned? +// parindex = pointer to vector of integers indexing the parameters +// in 'p' in the order specified by the 'paramnames' slot +// on output: +// lik = pointer to vector containing likelihoods + +// prototype for parameter transformation function. +typedef void pomp_transform_fn (double *pt, double *p, int *parindex); + #endif Modified: pkg/pomp/src/pomp.h =================================================================== --- pkg/pomp/src/pomp.h 2015-02-28 17:56:04 UTC (rev 1117) +++ pkg/pomp/src/pomp.h 2015-03-01 03:40:12 UTC (rev 1118) @@ -8,201 +8,9 @@ #include #include -// FACILITIES FOR EXTRACTING R OBJECTS FROM THE 'USERDATA' SLOT -const SEXP get_pomp_userdata (const char *name); -const int *get_pomp_userdata_int (const char *name); -const double *get_pomp_userdata_double (const char *name); - // FACILITY FOR EVALUATING A SET OF PERIODIC BSPLINE BASIS FUNCTIONS void periodic_bspline_basis_eval (double x, double period, int degree, int nbasis, double *y); -// PROTOTYPE FOR PARAMETER TRANSFORMATION FUNCTION. -typedef void pomp_transform_fn (double *pt, double *p, int *parindex); - -// PROTOTYPE FOR STOCHASTIC SIMULATION ALGORITHM REACTION-RATE FUNCTION, AS USED BY "GILLESPIE.SIM": -typedef double pomp_ssa_rate_fn(int j, double t, const double *x, const double *p, - int *stateindex, int *parindex, int *covindex, - int ncovar, double *covars); -// Description: -// on input: -// j = integer specifying the number of the reaction whose rate is desired -// t = time at which the rates are to be evaluated -// x = vector of state variables -// p = vector of parameters -// stateindex = pointer to vector of integers pointing to the states in 'x' in the order specified by -// the 'statenames' argument of 'SSA.simulator' -// parindex = pointer to vector of integers pointing to the parameters in 'p' in the order specified by -// the 'paramnames' argument of 'SSA.simulator' -// covindex = pointer to vector of integers pointing to the covariates in 'covars' in the order -// specified by the 'covarnames' argument of 'SSA.simulator' -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'SSA.simulator' -// returns the rate of the j-th reaction - -// PROTOTYPE FOR ONE-STEP SIMULATOR, AS USED BY "EULER.SIM" AND "ONESTEP.SIM": -typedef void pomp_onestep_sim(double *x, const double *p, - const int *stateindex, const int *parindex, const int *covindex, - int ncovars, const double *covars, - double t, double dt); -// Description: -// on input: -// x = pointer to state vector -// p = pointer to parameter vector -// stateindex = pointer to vector of integers pointing to the states in 'x' in the order specified by -// the 'statenames' argument of 'euler.simulator' -// parindex = pointer to vector of integers pointing to the parameters in 'p' in the order specified by -// the 'paramnames' argument of 'euler.simulator' -// covindex = pointer to vector of integers pointing to the covariates in 'covars' in the order -// specified by the 'covarnames' argument of 'euler.simulator' -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'euler.simulator' -// t = time at the beginning of the Euler step -// dt = size (duration) of the Euler step -// on output: -// x = contains the new state vector (i.e., at time t+dt) -// -// NB: There is no need to call GetRNGstate() or PutRNGstate() in the body of the user-defined function. -// The RNG is initialized before any call to this function, and the RNG state is written afterward. -// Inclusion of these calls in the user-defined function may result in significant slowdown. - - -// PROTOTYPE FOR ONE-STEP LOG PROBABILITY DENSITY FUNCTION, AS USED BY "ONESTEP.DENS": -typedef void pomp_onestep_pdf(double *f, - double *x1, double *x2, double t1, double t2, const double *p, - const int *stateindex, const int *parindex, const int *covindex, - int ncovars, const double *covars); -// Description: -// on input: -// x1 = pointer to state vector at time t1 -// x2 = pointer to state vector at time t2 -// t1 = time corresponding to x1 -// t2 = time corresponding to x2 -// p = pointer to parameter vector -// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by -// the 'statenames' argument of 'euler.density' -// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by -// the 'paramnames' argument of 'euler.density' -// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by -// the 'covarnames' argument of 'euler.density' -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'euler.density' -// on output: -// f = pointer to the probability density (a single scalar) - -// PROTOTYPE FOR DETERMINISTIC SKELETON EVALUATION -typedef void pomp_skeleton (double *f, double *x, double *p, - int *stateindex, int *parindex, int *covindex, - int ncovars, double *covars, double t); - -// Description: -// on input: -// x = pointer to state vector at time t -// p = pointer to parameter vector -// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by -// the 'statenames' slot -// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by -// the 'paramnames' slot -// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by -// the 'covarnames' slot -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'pomp.skeleton' -// t = time at the beginning of the Euler step -// on output: -// f = pointer to value of the map or vectorfield (a vector of the same length as 'x') - -// PROTOTYPE FOR MEASUREMENT MODEL SIMULATION -typedef void pomp_measure_model_simulator (double *y, double *x, double *p, - int *obsindex, int *stateindex, int *parindex, int *covindex, - int ncovars, double *covars, double t); -// Description: -// on input: -// x = pointer to state vector at time t -// p = pointer to parameter vector -// obsindex = pointer to vector of integers indexing the variables in 'y' in the order specified by -// the 'obsnames' slot -// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by -// the 'statenames' slot -// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by -// the 'paramnames' slot -// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by -// the 'covarnames' slot -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'pomp.skeleton' -// t = time at the beginning of the Euler step -// on output: -// y = pointer to vector containing simulated observations (length = nobs = nrow(data)) -// -// NB: There is no need to call GetRNGstate() or PutRNGstate() in the body of the user-defined function. -// The RNG is initialized before any call to this function, and the RNG state is written afterward. -// Inclusion of these calls in the user-defined function may result in significant slowdown. - - -// PROTOTYPE FOR MEASUREMENT MODEL DENSITY EVALUATOR -typedef void pomp_measure_model_density (double *lik, double *y, double *x, double *p, int give_log, - int *obsindex, int *stateindex, int *parindex, int *covindex, - int ncovars, double *covars, double t); -// Description: -// on input: -// y = pointer to vector of observables at time t -// x = pointer to state vector at time t -// p = pointer to parameter vector -// give_log = should the log likelihood be returned? -// obsindex = pointer to vector of integers indexing the variables in 'y' in the order specified by -// the 'obsnames' slot -// stateindex = pointer to vector of integers indexing the states in 'x' in the order specified by -// the 'statenames' slot -// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by -// the 'paramnames' slot -// covindex = pointer to vector of integers indexing the parameters in 'covar'' in the order specified by -// the 'covarnames' slot -// ncovars = number of covariates -// covars = pointer to a vector containing the values of the covariates at time t, as interpolated -// from the covariate table supplied to 'pomp.skeleton' -// t = time at the beginning of the Euler step -// on output: -// lik = pointer to scalar containing (log) likelihood - -// PROTOTYPE FOR PRIOR SIMULATION -typedef void pomp_rprior (double *p, int *parindex); -// Description: -// on input: -// p = pointer to parameter vector -// parindex = pointer to vector of integers indexing the parameters in 'p' in the order specified by -// the 'paramnames' slot -// on output: -// p = pointer to vector containing draws from the prior -// -// NB: There is no need to call GetRNGstate() or PutRNGstate() in the body of the user-defined function. -// The RNG is initialized before any call to this function, and the RNG state is written afterward. -// Inclusion of these calls in the user-defined function may result in significant slowdown. - -// PROTOTYPE FOR PRIOR DENSITY EVALUATION -typedef void pomp_dprior (double *lik, double *p, int give_log, int *parindex); -// Description: -// on input: -// p = pointer to parameter vector [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1118 From noreply at r-forge.r-project.org Sun Mar 1 04:40:57 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Sun, 1 Mar 2015 04:40:57 +0100 (CET) Subject: [Pomp-commits] r1119 - pkg/pomp/R pkg/pomp/inst pkg/pomp/inst/examples pkg/pomp/man pkg/pomp/tests www/content www/vignettes Message-ID: <20150301034058.0A337183C1E@r-forge.r-project.org> Author: kingaa Date: 2015-03-01 04:40:56 +0100 (Sun, 01 Mar 2015) New Revision: 1119 Removed: pkg/pomp/inst/examples/verhulst.R pkg/pomp/man/verhulst.Rd pkg/pomp/tests/verhulst.R pkg/pomp/tests/verhulst.Rout.save Modified: pkg/pomp/R/pomp-methods.R pkg/pomp/inst/NEWS pkg/pomp/inst/NEWS.Rd pkg/pomp/man/example.Rd pkg/pomp/tests/steps.R pkg/pomp/tests/steps.Rout.save www/content/NEWS.html www/vignettes/Makefile www/vignettes/index.html Log: - fix bug in partrans - remove 'verhulst' example - remove reference to 'advanced topics' vignette from webpage Modified: pkg/pomp/R/pomp-methods.R =================================================================== --- pkg/pomp/R/pomp-methods.R 2015-03-01 03:40:12 UTC (rev 1118) +++ pkg/pomp/R/pomp-methods.R 2015-03-01 03:40:56 UTC (rev 1119) @@ -28,8 +28,11 @@ partrans.internal <- function (object, params, dir = c("forward","inverse"), .getnativesymbolinfo = TRUE, ...) { if (!object at has.trans) return(params) + pompLoad(object) dir <- switch(match.arg(dir),forward=1L,inverse=-1L) - .Call(do_partrans,object,params,dir,.getnativesymbolinfo) + rv <- .Call(do_partrans,object,params,dir,.getnativesymbolinfo) + pompUnload(object) + rv } setMethod("partrans","pomp", @@ -310,4 +313,3 @@ invisible(NULL) } ) - Modified: pkg/pomp/inst/NEWS =================================================================== --- pkg/pomp/inst/NEWS 2015-03-01 03:40:12 UTC (rev 1118) +++ pkg/pomp/inst/NEWS 2015-03-01 03:40:56 UTC (rev 1119) @@ -1,5 +1,12 @@ _N_e_w_s _f_o_r _p_a_c_k_a_g_e '_p_o_m_p' +_C_h_a_n_g_e_s _i_n '_p_o_m_p' _v_e_r_s_i_o_n _0._6_2-_2: + + ? Bug fix in ?partrans? when transformations are implemented + using ?Csnippet?s. + + ? Remove the ?verhulst? example. + _C_h_a_n_g_e_s _i_n '_p_o_m_p' _v_e_r_s_i_o_n _0._6_2-_1: ? ?mif? now has the default value ?var.factor=1?. Since Modified: pkg/pomp/inst/NEWS.Rd =================================================================== --- pkg/pomp/inst/NEWS.Rd 2015-03-01 03:40:12 UTC (rev 1118) +++ pkg/pomp/inst/NEWS.Rd 2015-03-01 03:40:56 UTC (rev 1119) @@ -1,5 +1,11 @@ \name{NEWS} \title{News for package `pomp'} +\section{Changes in \pkg{pomp} version 0.62-2}{ + \itemize{ + \item Bug fix in \code{partrans} when transformations are implemented using \code{Csnippet}s. + \item Remove the \code{verhulst} example. + } +} \section{Changes in \pkg{pomp} version 0.62-1}{ \itemize{ \item \code{mif} now has the default value \code{var.factor=1}. Deleted: pkg/pomp/inst/examples/verhulst.R =================================================================== --- pkg/pomp/inst/examples/verhulst.R 2015-03-01 03:40:12 UTC (rev 1118) +++ pkg/pomp/inst/examples/verhulst.R 2015-03-01 03:40:56 UTC (rev 1119) @@ -1,1052 +0,0 @@ -require(pomp) - -dat <- '"time";"obs" -0,1;12476,9463966376 -0,2;10728,2422378213 -0,3;11398,0776385115 -0,4;12287,9670238814 -0,5;9012,37523428899 -0,6;8452,39753669702 -0,7;9704,7441287775 -0,8;8963,78424859124 -0,9;7829,66389402983 -1;7655,43492706061 -1,1;9309,04592787201 -1,2;7946,94132184123 -1,3;12108,6790891141 -1,4;14198,8647151384 -1,5;12927,6349958936 -1,6;16760,392326066 -1,7;11420,2006149761 -1,8;12798,0730275012 -1,9;11126,6555465736 -2;12268,966760168 -2,1;12889,140814792 -2,2;15717,842837741 -2,3;16476,4476949001 -2,4;13935,8229597974 -2,5;11274,5690427355 -2,6;12038,307109693 -2,7;16606,6627272479 -2,8;18198,4621610355 -2,9;17293,0054680149 -3;12523,849186477 -3,1;10313,2154355352 -3,2;9321,36401435259 -3,3;10799,8076207109 -3,4;10178,8374334587 -3,5;10045,1158889129 -3,6;11025,1281020003 -3,7;10169,2849982066 -3,8;8681,07015468727 -3,9;10732,796788325 -4;11036,7965511601 -4,1;11868,8147354882 -4,2;13625,7117038416 -4,3;11265,4772635401 -4,4;10141,6251649885 -4,5;10867,4578828498 -4,6;12785,2102229267 -4,7;11328,7462817584 -4,8;12631,6392612663 -4,9;11990,4877952651 -5;11707,021358751 -5,1;11467,9348717264 -5,2;11138,9674897421 -5,3;10828,0402696172 -5,4;10693,5753292854 -5,5;8070,20512554236 -5,6;7974,66822200446 -5,7;12124,8774955935 -5,8;10571,6897970932 -5,9;10408,3525902188 -6;9947,10683615605 -6,1;6761,26080348258 -6,2;7672,5615626058 -6,3;6700,89947532411 -6,4;9957,70955089761 -6,5;6984,15360685567 -6,6;8711,27713852725 -6,7;8845,09832738289 -6,8;6151,45542760105 -6,9;5909,9033310504 -7;5677,0462793129 -7,1;4685,26869088051 -7,2;6081,7401479026 -7,3;5140,81107070182 -7,4;5987,21047593122 -7,5;5958,39974011806 -7,6;5797,10888222691 -7,7;8969,30480435117 -7,8;7154,13424413776 -7,9;7001,79895206227 -8;6835,58722221115 -8,1;7178,49582555569 -8,2;7068,30093611577 -8,3;7477,13697964531 -8,4;8772,554138563 -8,5;8022,86659094765 -8,6;8372,0317907956 -8,7;10041,3593267306 -8,8;10253,050990357 -8,9;9043,82119751564 -9;10045,5914827808 -9,1;8645,9514960239 -9,2;7587,78596251839 -9,3;8050,67704946183 -9,4;12766,8084185733 -9,5;11320,2397899506 -9,6;11983,2137256095 -9,7;10346,5261277883 -9,8;10976,0207971127 -9,9;10596,5951721337 -10;12354,9165211917 -10,1;13176,0001734934 -10,2;10787,1844790958 -10,3;9016,89457113492 -10,4;9591,14684777673 -10,5;9326,59125815507 -10,6;8400,48447975349 -10,7;8103,47670668761 -10,8;6850,46195015796 -10,9;8523,22233334717 -11;7320,06708241798 -11,1;6761,31990109052 -11,2;10335,7413628739 -11,3;8452,63560033498 -11,4;7651,84663783688 -11,5;10973,5604541944 -11,6;9445,95763629494 -11,7;10218,29998992 -11,8;7766,96969085216 -11,9;7792,66151934471 -12;11724,2680465198 -12,1;9046,55821600569 -12,2;7933,82281121758 -12,3;8494,97595285483 -12,4;12847,3887298016 -12,5;10294,8960103345 -12,6;15253,0634118407 -12,7;14400,4899470299 -12,8;12691,4502676006 -12,9;12476,3346535563 -13;11290,0609563828 -13,1;11593,0442976639 -13,2;11445,9423045149 -13,3;10381,2431323292 -13,4;11264,5376923105 -13,5;11285,9320427566 -13,6;10710,3502098923 -13,7;10396,059083809 -13,8;10729,9941311348 -13,9;8584,80968880257 -14;9123,06769305207 -14,1;9551,82625036035 -14,2;12759,0676102405 -14,3;10886,7202223913 -14,4;8689,0430008371 -14,5;8601,59754664362 -14,6;9227,67154381367 -14,7;10759,4161716665 -14,8;8701,93376658181 -14,9;8694,06775689441 -15;7120,05485126926 -15,1;7871,86018020619 -15,2;11325,3190917209 -15,3;11031,3141538231 -15,4;8537,06017947308 -15,5;7721,65289483558 -15,6;12768,3261913139 -15,7;11373,8084037005 -15,8;7561,75216737958 -15,9;9022,9974341319 -16;10469,6335508079 -16,1;12518,4220722121 -16,2;15126,603804632 -16,3;11534,1997794343 -16,4;13622,6376508151 -16,5;9752,91900516775 -16,6;9571,21351591001 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-' - -pomp( - data=read.csv2(text=dat), - times="time", - t0=0, - params=c(n.0=10000,K=10000,r=0.9,sigma=0.4,tau=0.1), - rprocess=euler.sim( - step.fun=function(x,t,params,delta.t,...){ - r <- params["r"] - K <- params["K"] - sigma <- params["sigma"] - n <- x["n"] - rnorm( - n=1, - mean=n+r*n*(1-n/K)*delta.t, - sd=sigma*n*sqrt(delta.t) - ) - }, - delta.t=0.01 - ), - dprocess=onestep.dens( - dens.fun=function(x1,x2,t1,t2,params,log,...){ - delta.t <- t2-t1 - r <- params["r"] - K <- params["K"] - sigma <- params["sigma"] - n <- x1["n"] - dnorm( - x=x2["n"], - mean=n+r*n*(1-n/K)*delta.t, - sd=sigma*n*sqrt(delta.t), - log=log - ) - } - ), - measurement.model=obs~lnorm(meanlog=log(n),sdlog=log(1+tau)), - skeleton.type="vectorfield", - skeleton=function(x,t,params,...){ - r <- params["r"] - K <- params["K"] - n <- x["n"] - f <- r*n*(1-n/K) - names(f) <- "n" - f - } - ) -> verhulst - -c("verhulst") Modified: pkg/pomp/man/example.Rd =================================================================== --- pkg/pomp/man/example.Rd 2015-03-01 03:40:12 UTC (rev 1118) +++ pkg/pomp/man/example.Rd 2015-03-01 03:40:56 UTC (rev 1119) @@ -46,7 +46,7 @@ \code{\link{blowflies}}, \code{\link{dacca}}, \code{\link{gompertz}}, \code{\link{ou2}}, \code{\link{ricker}}, \code{\link{rw2}}, \code{\link{euler.sir}}, \code{\link{gillespie.sir}}, - \code{\link{bbs}}, \code{\link{verhulst}} + \code{\link{bbs}} } \keyword{models} \keyword{datasets} Deleted: pkg/pomp/man/verhulst.Rd =================================================================== --- pkg/pomp/man/verhulst.Rd 2015-03-01 03:40:12 UTC (rev 1118) +++ pkg/pomp/man/verhulst.Rd 2015-03-01 03:40:56 UTC (rev 1119) @@ -1,29 +0,0 @@ -\name{verhulst} -\alias{verhulst} -\docType{data} -\title{Simple Verhulst-Pearl (logistic) model.} -\description{ - \code{verhulst} is a \code{pomp} object encoding a univariate stochastic logistic model with measurement error. -} -\details{ - The model is written as an Ito diffusion, \deqn{dn = r n \left(1-\frac{n}{K}\right) dt + \sigma n dW}{dn = r n (1-n/K) dt + sigma n dW}, where \eqn{W} is a Wiener process. - It is implemented using the \code{\link{euler.sim}} plug-in. -} -\examples{ -pompExample(verhulst) -plot(verhulst) -coef(verhulst) -params <- cbind( - c(n.0=100,K=10000,r=0.2,sigma=0.4,tau=0.1), - c(n.0=1000,K=11000,r=0.1,sigma=0.4,tau=0.1) - ) -x <- simulate(verhulst,params=params,states=TRUE) -matplot(time(verhulst),t(x['n',,]),type='l') -y <- trajectory(verhulst,params=params) -matlines(time(verhulst),t(y['n',,]),type='l',lwd=2) -} -\seealso{ - \code{\link{pomp}} -} -\keyword{models} -\keyword{datasets} Modified: pkg/pomp/tests/steps.R =================================================================== --- pkg/pomp/tests/steps.R 2015-03-01 03:40:12 UTC (rev 1118) +++ pkg/pomp/tests/steps.R 2015-03-01 03:40:56 UTC (rev 1119) @@ -9,9 +9,8 @@ y <- simulate(ricker,times=tm,states=TRUE)["N",,] stopifnot(identical(x,y)) -pompExample(verhulst) -coef(verhulst,c("n.0","sigma")) <- c(15,0) +pompExample(euler.sir) tm <- sort(runif(n=100,max=1)) -x <- trajectory(verhulst,times=tm)["n",,] -y <- simulate(verhulst,times=tm,states=TRUE)["n",,] +x <- trajectory(euler.sir,times=tm)["I",,] +y <- simulate(euler.sir,times=tm,states=TRUE)["I",,] table(cut(x-y,breaks=c(-Inf,seq(-0.2,0.2,by=0.01),Inf),ordered=T)) Modified: pkg/pomp/tests/steps.Rout.save =================================================================== --- pkg/pomp/tests/steps.Rout.save 2015-03-01 03:40:12 UTC (rev 1118) +++ pkg/pomp/tests/steps.Rout.save 2015-03-01 03:40:56 UTC (rev 1119) @@ -30,17 +30,16 @@ > y <- simulate(ricker,times=tm,states=TRUE)["N",,] > stopifnot(identical(x,y)) > -> pompExample(verhulst) +> pompExample(euler.sir) newly created object(s): - verhulst -> coef(verhulst,c("n.0","sigma")) <- c(15,0) + euler.sir > tm <- sort(runif(n=100,max=1)) -> x <- trajectory(verhulst,times=tm)["n",,] -> y <- simulate(verhulst,times=tm,states=TRUE)["n",,] +> x <- trajectory(euler.sir,times=tm)["I",,] +> y <- simulate(euler.sir,times=tm,states=TRUE)["I",,] > table(cut(x-y,breaks=c(-Inf,seq(-0.2,0.2,by=0.01),Inf),ordered=T)) (-Inf,-0.2] (-0.2,-0.19] (-0.19,-0.18] (-0.18,-0.17] (-0.17,-0.16] - 0 0 0 0 0 + 96 0 0 0 0 (-0.16,-0.15] (-0.15,-0.14] (-0.14,-0.13] (-0.13,-0.12] (-0.12,-0.11] 0 0 0 0 0 (-0.11,-0.1] (-0.1,-0.09] (-0.09,-0.08] (-0.08,-0.07] (-0.07,-0.06] @@ -48,16 +47,16 @@ (-0.06,-0.05] (-0.05,-0.04] (-0.04,-0.03] (-0.03,-0.02] (-0.02,-0.01] 0 0 0 0 0 (-0.01,0] (0,0.01] (0.01,0.02] (0.02,0.03] (0.03,0.04] - 0 13 11 11 8 + 0 0 0 0 0 (0.04,0.05] (0.05,0.06] (0.06,0.07] (0.07,0.08] (0.08,0.09] - 13 13 8 3 3 + 0 0 0 0 0 (0.09,0.1] (0.1,0.11] (0.11,0.12] (0.12,0.13] (0.13,0.14] - 11 6 0 0 0 + 0 0 0 0 0 (0.14,0.15] (0.15,0.16] (0.16,0.17] (0.17,0.18] (0.18,0.19] 0 0 0 0 0 (0.19,0.2] (0.2, Inf] - 0 0 + 0 4 > > proc.time() user system elapsed - 0.632 0.044 0.697 + 0.570 0.030 0.587 Deleted: pkg/pomp/tests/verhulst.R =================================================================== --- pkg/pomp/tests/verhulst.R 2015-03-01 03:40:12 UTC (rev 1118) +++ pkg/pomp/tests/verhulst.R 2015-03-01 03:40:56 UTC (rev 1119) @@ -1,11 +0,0 @@ -library(pomp) - -pompExample(verhulst) - -tail(as(verhulst,"data.frame")) -tail(as.data.frame(verhulst)) - -coef(verhulst,c("n.0","sigma")) <- c(100,0.2) -time(verhulst) <- 1:100 - -tail(as.data.frame(simulate(verhulst,seed=1066L))) Deleted: pkg/pomp/tests/verhulst.Rout.save =================================================================== --- pkg/pomp/tests/verhulst.Rout.save 2015-03-01 03:40:12 UTC (rev 1118) +++ pkg/pomp/tests/verhulst.Rout.save 2015-03-01 03:40:56 UTC (rev 1119) @@ -1,57 +0,0 @@ - -R version 3.1.2 (2014-10-31) -- "Pumpkin Helmet" -Copyright (C) 2014 The R Foundation for Statistical Computing -Platform: x86_64-unknown-linux-gnu (64-bit) - -R is free software and comes with ABSOLUTELY NO WARRANTY. -You are welcome to redistribute it under certain conditions. -Type 'license()' or 'licence()' for distribution details. - -R is a collaborative project with many contributors. -Type 'contributors()' for more information and -'citation()' on how to cite R or R packages in publications. - -Type 'demo()' for some demos, 'help()' for on-line help, or -'help.start()' for an HTML browser interface to help. -Type 'q()' to quit R. - -> library(pomp) -Loading required package: subplex -Loading required package: nloptr -> -> pompExample(verhulst) -newly created object(s): - verhulst -> -> tail(as(verhulst,"data.frame")) - time obs -995 99.5 14051.372 -996 99.6 10764.397 -997 99.7 8359.591 -998 99.8 8337.105 -999 99.9 8322.998 -1000 100.0 8327.300 -> tail(as.data.frame(verhulst)) - time obs -995 99.5 14051.372 -996 99.6 10764.397 -997 99.7 8359.591 -998 99.8 8337.105 -999 99.9 8322.998 -1000 100.0 8327.300 -> -> coef(verhulst,c("n.0","sigma")) <- c(100,0.2) -> time(verhulst) <- 1:100 -> -> tail(as.data.frame(simulate(verhulst,seed=1066L))) - time obs n -95 95 11528.048 10993.019 -96 96 7829.730 9218.963 -97 97 9483.337 9642.360 -98 98 9819.607 8914.544 -99 99 8753.751 9082.258 -100 100 9202.150 9452.477 -> -> proc.time() - user system elapsed - 0.696 0.044 0.755 Modified: www/content/NEWS.html =================================================================== --- www/content/NEWS.html 2015-03-01 03:40:12 UTC (rev 1118) +++ www/content/NEWS.html 2015-03-01 03:40:56 UTC (rev 1119) @@ -8,6 +8,19 @@

News for package ‘pomp’

+

Changes in pomp version 0.62-2

+ + +
    +

  • Bug fix in partrans when transformations are implemented using Csnippets. +

    +
    • +

  • Remove the verhulst example. +

    +
+ + + [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1119 From noreply at r-forge.r-project.org Sun Mar 1 04:41:10 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Sun, 1 Mar 2015 04:41:10 +0100 (CET) Subject: [Pomp-commits] r1120 - www/vignettes Message-ID: <20150301034110.A3ECF183C1E@r-forge.r-project.org> Author: kingaa Date: 2015-03-01 04:41:09 +0100 (Sun, 01 Mar 2015) New Revision: 1120 Added: www/vignettes/getting_started.R www/vignettes/getting_started.Rmd www/vignettes/getting_started.html Modified: www/vignettes/Makefile www/vignettes/pomp.bib www/vignettes/pomp.pdf Log: - remove advanced topics vignette - add getting_started vignette - update Makefile Modified: www/vignettes/Makefile =================================================================== --- www/vignettes/Makefile 2015-03-01 03:40:56 UTC (rev 1119) +++ www/vignettes/Makefile 2015-03-01 03:41:09 UTC (rev 1120) @@ -7,7 +7,7 @@ default: vignettes clean -vignettes: advanced_topics_in_pomp.pdf advanced_topics_in_pomp.R intro_to_pomp.pdf intro_to_pomp.R +vignettes: intro_to_pomp.pdf intro_to_pomp.R getting_started.html getting_started.R %.R: %.Rnw $(RSCRIPT) -e 'library(knitr); purl("$*.Rnw")' @@ -15,6 +15,9 @@ %.tex: %.Rnw $(RSCRIPT) -e 'library(knitr); knit("$*.Rnw")' +%.R: %.Rmd + $(RSCRIPT) -e 'library(knitr); purl("$*.Rmd")' + %.pdf: %.tex $(PDFLATEX) $* -$(BIBTEX) $* @@ -27,4 +30,3 @@ $(RM) -r cache figure $(RM) *.c *.o *.so *.bak $(RM) Rplots.pdf - $(RM) -r figure Added: www/vignettes/getting_started.R =================================================================== --- www/vignettes/getting_started.R (rev 0) +++ www/vignettes/getting_started.R 2015-03-01 03:41:09 UTC (rev 1120) @@ -0,0 +1,215 @@ +## ----opts,include=FALSE-------------------------------------------------- +library(knitr) +prefix <- "getting-started" +opts_chunk$set( + progress=TRUE, + prompt=FALSE,tidy=FALSE,highlight=TRUE, + strip.white=TRUE, + warning=FALSE, + message=FALSE, + error=FALSE, + echo=TRUE, + cache=TRUE, + results='markup', + fig.show='asis', + size='small', + fig.lp="fig:", + fig.path=paste0("figure/",prefix,"-"), + cache.path=paste0("cache/",prefix,"-"), + fig.pos="h!", + fig.align='center', + fig.height=4,fig.width=6.83, + out.width="\\linewidth", + dpi=300, + dev='png', + dev.args=list(bg='transparent') + ) + +## ----prelims,echo=F,cache=F---------------------------------------------- +set.seed(594709947L) +require(ggplot2) +require(plyr) +require(reshape2) +require(magrittr) +require(pomp) +theme_set(theme_bw()) +stopifnot(packageVersion("pomp")>="0.62-1") +options( + keep.source=TRUE, + stringsAsFactors=FALSE, + encoding="UTF-8" + ) + +## ----eval=FALSE---------------------------------------------------------- +## install.packages("pomp",repos="http://R-Forge.R-Project.org") + +## ----eval=FALSE---------------------------------------------------------- +## cat("#include +## void hello (void) { +## Rprintf(\"hello world!\\n\"); +## }",file="hello.c") +## system("R CMD SHLIB hello.c") +## dyn.load(paste0("hello",.Platform$dynlib.ext)) +## .C("hello",PACKAGE="hello") + +## ----load-parus-data----------------------------------------------------- +parus.dat <- read.csv(text=" + year,pop + 1960,148 + 1961,258 + 1962,185 + 1963,170 + 1964,267 + 1965,239 + 1966,196 + 1967,132 + 1968,167 + 1969,186 + 1970,128 + 1971,227 + 1972,174 + 1973,177 + 1974,137 + 1975,172 + 1976,119 + 1977,226 + 1978,166 + 1979,161 + 1980,199 + 1981,306 + 1982,206 + 1983,350 + 1984,214 + 1985,175 + 1986,211" + ) + +## ----parus-plot---------------------------------------------------------- +ggplot(data=parus.dat,mapping=aes(x=year,y=pop))+ + geom_line()+geom_point()+ + expand_limits(y=0)+ + theme_classic() + +## ----logistic-step-fun--------------------------------------------------- +step.fun <- Csnippet(" + double dW = rnorm(0,sqrt(dt)); + N += r*N*(1-N/K)*dt+sigma*N*dW; + ") + +## ----logistic-pomp1,cache=FALSE------------------------------------------ +parus <- pomp(data=parus.dat,time="year",t0=1959, + rprocess=euler.sim(step.fun=step.fun,delta.t=1/365), + statenames="N",paramnames=c("r","K","sigma")) + +## ----logistic-simul1----------------------------------------------------- +simStates <- simulate(parus,nsim=10,params=c(r=0.2,K=200,sigma=0.5,N.0=200),states=TRUE) + +## ----logistic-plot1,echo=FALSE------------------------------------------- +melt(simStates) %>% + dcast(rep+time~variable) %>% + ggplot(mapping=aes(x=time,y=N,group=rep,color=factor(rep)))+ + geom_line()+guides(color=FALSE)+ + theme_classic() + +## ----logistic-rmeasure--------------------------------------------------- +rmeas <- Csnippet(" + pop = rpois(phi*N); + ") + +## ----logistic-pomp2,cache=FALSE------------------------------------------ +parus <- pomp(parus,rmeasure=rmeas,paramnames="phi",statenames="N") + +## ----logistic-simul2----------------------------------------------------- +sim <- simulate(parus,params=c(r=0.2,K=200,phi=0.5,sigma=0.5,N.0=200), + nsim=10,obs=TRUE,states=TRUE) + +## ----logistic-plot2,echo=FALSE------------------------------------------- +sim %>% melt() %>% + ggplot(mapping=aes(x=time,y=value,group=rep,color=factor(rep)))+ + geom_line()+ + guides(color=FALSE)+scale_y_sqrt()+ + facet_grid(variable~.,scales="free_y") + +sim %>% melt() %>% dcast(rep+time~variable,value.var='value') %>% + ggplot(mapping=aes(x=N,y=pop,color=factor(rep)))+ + geom_point()+scale_x_sqrt()+scale_y_sqrt()+ + coord_equal()+ + guides(color=FALSE) + +## ----logistic-dmeasure--------------------------------------------------- +dmeas <- Csnippet(" + lik = dpois(pop,phi*N,give_log); + ") + +## ----logistic-pomp3,cache=FALSE------------------------------------------ +parus <- pomp(parus,dmeasure=dmeas,paramnames="phi",statenames="N") + +## ----logistic-pfilter---------------------------------------------------- +pf <- pfilter(parus,Np=1000,params=c(r=0.2,K=200,phi=0.5,sigma=0.5,N.0=200)) +logLik(pf) + +## ----logistic-skeleton,cache=FALSE--------------------------------------- +skel <- Csnippet(" + DN = r*N*(1-N/K); + ") + +parus <- pomp(parus,skeleton=skel,skeleton.type="vectorfield",statenames="N",paramnames=c("r","K")) + +## ----logistic-traj1------------------------------------------------------ +pars <- parmat(c(r=1,K=200,phi=0.5,sigma=0.5,N.0=20),5) +pars["N.0",] <- seq(20,300,length=5) +traj <- trajectory(parus,params=pars,times=seq(1959,1970,by=0.01)) + +## ----logistic-plot3,echo=FALSE------------------------------------------- +trajectory(parus,params=pars,times=seq(1959,1970,by=0.01),as.data.frame=TRUE) %>% + ggplot(mapping=aes(x=time,y=N,group=traj,color=traj))+ + guides(color=FALSE)+ + geom_line() + +## ----bh-stepfun---------------------------------------------------------- +bh.step <- Csnippet(" + double eps = rlnorm(-sigma*sigma/2,sigma); + N = a*N/(1+b*N)*eps; + ") + +## ----bh-skeleton--------------------------------------------------------- +bh.skel <- Csnippet(" + DN = a*N/(1+b*N); + ") + +## ----bh-pomp1,cache=FALSE------------------------------------------------ +parus.bh <- pomp(parus,rprocess=discrete.time.sim(bh.step,delta.t=1),skeleton=bh.skel,skeleton.type="map",skelmap.delta.t=1,statenames="N",paramnames=c("a","b","sigma")) + +## ----bh-test------------------------------------------------------------- +coef(parus.bh) <- c(a=1.1,b=5e-4,sigma=0.5,N.0=30,phi=1) +sim <- simulate(parus.bh) +traj <- trajectory(parus.bh) +pf <- pfilter(parus.bh,Np=1000) + +## ----logistic-partrans,cache=FALSE--------------------------------------- +partrans <- Csnippet(" + Tr = exp(r); + TK = exp(K); + ") + +parinvtrans <- Csnippet(" + Tr = log(r); + TK = log(K); + ") + +parus <- pomp(parus,parameter.transform=partrans,parameter.inv.transform=parinvtrans, + paramnames=c("r","K")) + +## ----logistic-partrans-test,include=FALSE,cache=FALSE-------------------- +p <- c(r=1,K=200,phi=1,N.0=200,sigma=0.5) +coef(parus,transform=TRUE) <- partrans(parus,p,dir="inv") +stopifnot(all.equal(p,coef(parus))) + +## ----tempfile-view,eval=FALSE-------------------------------------------- +## op <- options(verbose=TRUE) +## +## parus <- pomp(data=parus.dat,times="year",t0=1959,rprocess=euler.sim(step.fun,delta.t=1/365), +## dmeasure=dmeas,rmeasure=rmeas,statenames="N",paramnames=c("r","phi","K","N.0","sigma")) +## +## options(op) + Added: www/vignettes/getting_started.Rmd =================================================================== --- www/vignettes/getting_started.Rmd (rev 0) +++ www/vignettes/getting_started.Rmd 2015-03-01 03:41:09 UTC (rev 1120) @@ -0,0 +1,461 @@ +--- +title: "Getting started with pomp" +author: "Aaron A. King" +date: "02/28/2015" +output: + html_document: + theme: flatly + toc: yes +bibliography: pomp.bib +csl: ecology.csl +--- + +Licensed under the [Creative Commons attribution-noncommercial license](http://creativecommons.org/licenses/by-nc/3.0). +Please share and remix noncommercially, mentioning its origin. +![CC-BY_NC](http://pomp.r-forge.r-project.org/graphics/cc-by-nc.png) + +```{r opts,include=FALSE} +library(knitr) +prefix <- "getting-started" +opts_chunk$set( + progress=TRUE, + prompt=FALSE,tidy=FALSE,highlight=TRUE, + strip.white=TRUE, + warning=FALSE, + message=FALSE, + error=FALSE, + echo=TRUE, + cache=TRUE, + results='markup', + fig.show='asis', + size='small', + fig.lp="fig:", + fig.path=paste0("figure/",prefix,"-"), + cache.path=paste0("cache/",prefix,"-"), + fig.pos="h!", + fig.align='center', + fig.height=4,fig.width=6.83, + out.width="\\linewidth", + dpi=300, + dev='png', + dev.args=list(bg='transparent') + ) +``` + + +```{r prelims,echo=F,cache=F} +set.seed(594709947L) +require(ggplot2) +require(plyr) +require(reshape2) +require(magrittr) +require(pomp) +theme_set(theme_bw()) +stopifnot(packageVersion("pomp")>="0.62-1") +options( + keep.source=TRUE, + stringsAsFactors=FALSE, + encoding="UTF-8" + ) +``` + +## Partially observed Markov process (POMP) models + +As its name implies `pomp` is focused on partially observed Markov process models. +These are also known as state-space model, hidden Markov models, and stochastic dynamical systems models. +Such models consist of an unobserved stochastic *state process*, connected to the data via an explicit model of the observation process. +We refer to the former as the *process model* and the latter as the *measurement model*. +Each model is, in fact, a probability distribution. +If we let $Y_t$ denote the measurement process at time $t$ and $X_t$ the state process, then by definition, the process model is determined by the density $f_{X_t|X_{t-1}}$ and the measurement process by the density $f_{Y_t|X_t}$. +We think of the data, $y^*_t$, $t=1,\dots,T$ as being a single realization of the $Y$ process. +To implement a POMP model in `pomp`, we have to specify the measurement and process distributions. + +Note however, that, for each of the process and the measurement model there are two distinct operations that we might wish to perform: + +1. we might wish to *simulate*, i.e., to draw a (pseudo)random sample from the distribution, or +2. we might wish to *evaluate the density* itself at given values of $X_t$ and/or $Y_t$. + +We refer to the simulation of $f_{X_t|X_{t-1}}$ as the *rprocess* component of the POMP model, the evaluation of $f_{X_t|X_{t-1}}$ as the *dprocess* component, the simulation of $f_{Y_t|X_t}$, as the *rmeasure* component, and the evaluation of $f_{Y_t|X_t}$ as the *dmeasure* component. +Methods that make no use of the *dprocess* component are called "plug-and-play" methods. +At present, `pomp` is focused on such methods, so there is no reason to focus on the dprocess component any further. +In the following, we will illustrate and explain how one specifies the rprocess, rmeasure, and dmeasure components of a model in `pomp`. +We will illustrate this using some simple examples. + +----------------------------------- +![schematic1](http://pomp.r-forge.r-project.org/graphics/state_space_diagram1.png) + +Schematic of the structure of a POMP showing causal relations and direction of information flow. +**The key perspective to keep in mind is that the model is to be viewed as the process that generated the data.** + +----------------------------------- +![schematic2](http://pomp.r-forge.r-project.org/graphics/state_space_diagram2.png) + +Another POMP model schematic, showing dependence among model variables. +State variables, $x$, at time $t$ depend only on state variables at the previous timestep. +Measurements, $y$, at time $t$ depend only on the state at that time. +Formally, $\mathrm{Prob}[X_t|X_1,\dots,X_{t-1},Y_1,\dots,Y_{t-1}]=\mathrm{Prob}[X_t|X_{t-1}]$ and $\mathrm{Prob}[Y_t|X_1,\dots,X_{t},Y_1,\dots,Y_{t-1}]=\mathrm{Prob}[Y_t|X_{t}]$ for all $t=1,\dots,T$. + +----------------------------------- + +## Preliminaries + +### Installing the package + +To get started, we must install `pomp`, if it is not already installed. +The package can be downloaded from CRAN, but the latest version is always available at the package homepage on R-Forge. +Run the following to install this to download and install the latest version. +```{r eval=FALSE} +install.packages("pomp",repos="http://R-Forge.R-Project.org") +``` + +### Important information for Windows and Mac users. + +In this document, we will implement `pomp` models using the package's `Csnippet` facility. +This allows the user to write model components using snippets of C code, which is then compiled and linked into a running `R` session. +This typically affords a manyfold increase in computation time. +It is possible to avoid `Csnippet`s entirely by writing model components as `R` functions, but the resulting implementations are typically too slow to be of practical use. + +**Note to Windows users.** +To use `Csnippet`s, you must be able to compile C codes. +Compilers are not typically installed on Windows systems. +To achieve full functionality of `pomp` on a Windows computer, therefore, you must install the `Rtools` suite. +See http://cran.r-project.org/bin/windows/Rtools for downloads and instructions. + +**Note to Mac users.** +Although a variety of compilers are freely available for the Mac platform, they are not typically installed by default. + +The `Csnippet` functionality in essence requires that you be able to use `R CMD SHLIB`. +To see if you can do this, execute the following in an `R` session. +```{r eval=FALSE} +cat("#include + void hello (void) { + Rprintf(\"hello world!\\n\"); + }",file="hello.c") +system("R CMD SHLIB hello.c") +dyn.load(paste0("hello",.Platform$dynlib.ext)) +.C("hello",PACKAGE="hello") +``` +If you see the "hello world" message printed, your system should support `Csnippet`. + + +### Loading data + +We will illustrate `pomp` by performing a limited data analysis on a set of bird abundance data. +The data are from annual censuses of a population of *Parus major* (Great Tit) in Wytham Wood, Oxfordshire. +They were retrieved as dataset #10163 from the Global Population Dynamics Database version 2 (NERC Centre for Population Biology, Imperial College, 2010). +The original source is @McCleery1991. + +We load the data by doing +```{r load-parus-data} +parus.dat <- read.csv(text=" + year,pop + 1960,148 + 1961,258 + 1962,185 + 1963,170 + 1964,267 + 1965,239 + 1966,196 + 1967,132 + 1968,167 + 1969,186 + 1970,128 + 1971,227 + 1972,174 + 1973,177 + 1974,137 + 1975,172 + 1976,119 + 1977,226 + 1978,166 + 1979,161 + 1980,199 + 1981,306 + 1982,206 + 1983,350 + 1984,214 + 1985,175 + 1986,211" + ) +``` + +Here is a plot of these data: + +```{r parus-plot} +ggplot(data=parus.dat,mapping=aes(x=year,y=pop))+ + geom_line()+geom_point()+ + expand_limits(y=0)+ + theme_classic() +``` + +## Specifying a continuous-time process model + +To keep things simple, let's attempt to explain these data using a very simple model of stable but stochastic population dynamics, the logistic, or Verhulst-Pearl, equation with environmental stochasticity. +We'll write this model as a stochastic differential equation (SDE), specifically an Ito diffusion: +$$dN = r\,N\,\left(1-\frac{N}{K}\right)\,dt+\sigma\,N\,dW(t),$$ +where $N$ is the population size, $r$ is a fixed rate, the so-called "Malthusian parameter", $K$ is the population's "carrying capacity", $\sigma$ describes the intensity of extrinsic stochastic forcing on the system, and $dW$ is an increment of a standard Wiener process. +[Those unfamiliar with Wiener processes and Ito diffusions will find it useful to visualize $dW(t)$, for each time $t$, as a normal random variable with mean zero and standard deviation $\sqrt{dt}$.] +To implement this model in `pomp`, we must tell the package how to simulate this model. +The easiest way to simulate such an SDE is via the *Euler-Maruyama* method. +In this approximation, we take a large number of very small steps, each of duration $\Delta t$. +At each step, we hold the right-hand side of the above equation constant, compute $\Delta N$ using that equation, and increment $N$ accordingly. +`pomp` gives us the `euler.sim` function to assist us in implementing the Euler-Maruyama method. +To use it, we must encode the computations that take a single step. +The best way to do this is to write a snippet of code in the C language. +The following is such a snippet for the stochastic logistic equation above. + +```{r logistic-step-fun} +step.fun <- Csnippet(" + double dW = rnorm(0,sqrt(dt)); + N += r*N*(1-N/K)*dt+sigma*N*dW; + ") +``` + +This is just a snippet of C code: not all the variables are declared and the context of the snippet is not specified. +When given this snippet, `pomp` will provide the necessary declarations and context, compile the resulting C code, dynamically link to it, and use it to simulate realizations of the process model. +We cause all this to happen when we construct an object of class `pomp` via a call to the constructor function, which is also named `pomp`: + +```{r logistic-pomp1,cache=FALSE} +parus <- pomp(data=parus.dat,time="year",t0=1959, + rprocess=euler.sim(step.fun=step.fun,delta.t=1/365), + statenames="N",paramnames=c("r","K","sigma")) +``` + +In the above, we've specified an Euler-Maruyama time-step of about one day. +The `t0` argument specifies that we are going to treat the stochastic state process as being initialized in year 1959. +We use the `statenames` and `paramnames` arguments to indicate which of the undeclared variables in the `Csnippet` `step.fun` are state variables and which are fixed parameters. +Since `dW` is a local variable, we must provide an ordinary C declaration for it. +Note that `dt` is a variable that is defined in the context of this snippet; it is actually provided by `pomp` and will contain the size of the Euler step. +The `rnorm` function is part of the [`R` API](http://cran.r-project.org/doc/manuals/r-release/R-exts.html#The-R-API): see the [manual on "Writing R Extensions"](http://cran.r-project.org/doc/manuals/r-release/R-exts.html) for a description of this and the other [distribution functions provided as part of the `R` API](http://cran.r-project.org/doc/manuals/r-release/R-exts.html#Distribution-functions). +Finally, note that the state variable `N` is over-written by this snippet: it's value when the first line is executed is overwritten by the second line. + +[A full set of rules for writing `pomp` C snippets is given below][rules]. + +With the process model in place, we can simulate the process model using the `simulate` function and plot several realizations for a given set of parameters. + +```{r logistic-simul1} +simStates <- simulate(parus,nsim=10,params=c(r=0.2,K=200,sigma=0.5,N.0=200),states=TRUE) +``` +```{r logistic-plot1,echo=FALSE} +melt(simStates) %>% + dcast(rep+time~variable) %>% + ggplot(mapping=aes(x=time,y=N,group=rep,color=factor(rep)))+ + geom_line()+guides(color=FALSE)+ + theme_classic() +``` + + +## Specifying the measurement model + +Although it is the process model that is usually the focus of an investigator's interest, the measurement model is equally important because it connects the process model to the data. +For this example, let's model the observations using a Poisson distribution: +$$\mathrm{pop}_t \sim \mathrm{Poisson}(\phi\,N),$$ +where $\mathrm{pop}_t$ is our census population size at time $t$, $N$ is the true population size, and $\phi$ is a scaling parameter. + +### The rmeasure component + +The following snippet encodes the rmeasure component for this model. +```{r logistic-rmeasure} +rmeas <- Csnippet(" + pop = rpois(phi*N); + ") +``` +In this snippet of code, `N` is the state variable, `phi` is another parameter, and `pop` is the name of our observable, as defined in the dataset `parus.dat`. +The `rpois` function is part of the [`R` API](http://cran.r-project.org/doc/manuals/r-release/R-exts.html#The-R-API): it takes a single argument---the Poisson distribution's parameter---and returns a pseudo-random draw from the Poisson distribution with that parameter. +As with the `step.fun` snippet above, execution of this snippet causes `pop` to be overwritten. + +To fold this into our `pomp` object, we do +```{r logistic-pomp2,cache=FALSE} +parus <- pomp(parus,rmeasure=rmeas,paramnames="phi",statenames="N") +``` +Note that, again, we must tell `pomp` which of the variables is a parameter and which is a state variable. +We can now simulate from the full POMP model and plot the results. +```{r logistic-simul2} +sim <- simulate(parus,params=c(r=0.2,K=200,phi=0.5,sigma=0.5,N.0=200), + nsim=10,obs=TRUE,states=TRUE) +``` +```{r logistic-plot2,echo=FALSE} +sim %>% melt() %>% + ggplot(mapping=aes(x=time,y=value,group=rep,color=factor(rep)))+ + geom_line()+ + guides(color=FALSE)+scale_y_sqrt()+ + facet_grid(variable~.,scales="free_y") + +sim %>% melt() %>% dcast(rep+time~variable,value.var='value') %>% + ggplot(mapping=aes(x=N,y=pop,color=factor(rep)))+ + geom_point()+scale_x_sqrt()+scale_y_sqrt()+ + coord_equal()+ + guides(color=FALSE) +``` + +### The dmeasure component + +The following snippet encodes the dmeasure component. +```{r logistic-dmeasure} +dmeas <- Csnippet(" + lik = dpois(pop,phi*N,give_log); + ") +``` +and we fold it into the `pomp` object via +```{r logistic-pomp3,cache=FALSE} +parus <- pomp(parus,dmeasure=dmeas,paramnames="phi",statenames="N") +``` + +In the `dmeas` snippet, `dpois` again comes from the [`R` API](http://cran.r-project.org/doc/manuals/r-release/R-exts.html#The-R-API). +It takes three arguments, the datum, the Poisson parameter, and `give_log`. +When `give_log=0`, `dpois` returns the Poisson likelihood; +when `give_log=1`, `dpois` returns the log of this likelihood. +When this snippet is executed, `pomp` will provide the value of `give_log` according to its needs. +It is the user's responsibility to make sure that the correct value is returned. + +Since we now have both the rprocess and the dmeasure components in place, we can perform a particle filtering operation to estimate the log likelihood at any given point in parameter space. +For example, we can do +```{r logistic-pfilter} +pf <- pfilter(parus,Np=1000,params=c(r=0.2,K=200,phi=0.5,sigma=0.5,N.0=200)) +logLik(pf) +``` + +## A continuous-time deterministic skeleton + +A deterministic skeleton of the logistic model is obtained by taking $\sigma\to 0$, which leads to the deterministic differential equation +$$\frac{dN}{dt} = r\,N\,\left(1-\frac{N}{K}\right).$$ +The following snippet encodes this deterministic skeleton and folds it into the `pomp` object. +```{r logistic-skeleton,cache=FALSE} +skel <- Csnippet(" + DN = r*N*(1-N/K); + ") + +parus <- pomp(parus,skeleton=skel,skeleton.type="vectorfield",statenames="N",paramnames=c("r","K")) +``` +Note that in this snippet, `DN` is filled with the value of the time-derivative of `N`. +[See below for a complete set of rules for writing C snippets for `pomp`][rules]. + +With the deterministic skeleton in place we can generate several trajectories of the skeleton using `trajectory`, as follows, and plot the result. +```{r logistic-traj1} +pars <- parmat(c(r=1,K=200,phi=0.5,sigma=0.5,N.0=20),5) +pars["N.0",] <- seq(20,300,length=5) +traj <- trajectory(parus,params=pars,times=seq(1959,1970,by=0.01)) +``` +```{r logistic-plot3,echo=FALSE} +trajectory(parus,params=pars,times=seq(1959,1970,by=0.01),as.data.frame=TRUE) %>% + ggplot(mapping=aes(x=time,y=N,group=traj,color=traj))+ + guides(color=FALSE)+ + geom_line() +``` + +## Specifying a discrete-time process model and skeleton + +Let us demonstrate the implementation of discrete-time process models by replacing the continuous-time logistic equation used above with the stochastic Beverton-Holt model +$$N_{t+1}=\frac{a\,N_t}{1+b\,N_t}\,\varepsilon_t,$$ +where $a$ and $b$ are parameters and $\varepsilon_t\sim\mathrm{Lognormal}(-\tfrac{1}{2}\sigma^2,\sigma)$. + +Since we are now dealing with a discrete-time model, `euler.sim` will no longer construct an appropriate rprocess component. +Instead, we can use `discrete.time.sim`, which also takes a C snippet encoding the one-step simulation. +The following snippet simulates a single iteration of the stochastic Beverton-Holt map +```{r bh-stepfun} +bh.step <- Csnippet(" + double eps = rlnorm(-sigma*sigma/2,sigma); + N = a*N/(1+b*N)*eps; + ") +``` +A corresponding skeleton is the deterministic Beverton-Holt map obtained by setting $e_t=1$ in the above equation. +A snippet that implements this map is +```{r bh-skeleton} +bh.skel <- Csnippet(" + DN = a*N/(1+b*N); + ") +``` +Note that, as in the continuous case, we indicate the new value of the state variable by prepending `D` to the variable name. + +We create a new `pomp` object based on this process model but with the same rmeasure and dmeasure components as in `parus` by executing +```{r bh-pomp1,cache=FALSE} +parus.bh <- pomp(parus,rprocess=discrete.time.sim(bh.step,delta.t=1),skeleton=bh.skel,skeleton.type="map",skelmap.delta.t=1,statenames="N",paramnames=c("a","b","sigma")) +``` +The following codes compute some simulations, a trajectory of the skeleton, and run a particle filtering operation. +```{r bh-test} +coef(parus.bh) <- c(a=1.1,b=5e-4,sigma=0.5,N.0=30,phi=1) +sim <- simulate(parus.bh) +traj <- trajectory(parus.bh) +pf <- pfilter(parus.bh,Np=1000) +``` + +## Parameter transformations + +We can specify model-specific parameter transformations using C snippets. +The following implements log transformation of the $r$ and $K$ parameters of the logistic model and folds them into the `pomp` object `parus`. +```{r logistic-partrans,cache=FALSE} +partrans <- Csnippet(" + Tr = exp(r); + TK = exp(K); + ") + +parinvtrans <- Csnippet(" + Tr = log(r); + TK = log(K); + ") + +parus <- pomp(parus,parameter.transform=partrans,parameter.inv.transform=parinvtrans, + paramnames=c("r","K")) +``` +```{r logistic-partrans-test,include=FALSE,cache=FALSE} +p <- c(r=1,K=200,phi=1,N.0=200,sigma=0.5) +coef(parus,transform=TRUE) <- partrans(parus,p,dir="inv") +stopifnot(all.equal(p,coef(parus))) +``` + +## Rules for writing C snippets + +To fully understand how `pomp` makes use of C snippets, it is informative to have a look at the C file created by any call to `pomp` involving one or more C snippets. +Run the following in an `R` session and view the C file that is created in the session's temporary directory. +```{r tempfile-view,eval=FALSE} +op <- options(verbose=TRUE) + +parus <- pomp(data=parus.dat,times="year",t0=1959,rprocess=euler.sim(step.fun,delta.t=1/365), + dmeasure=dmeas,rmeasure=rmeas,statenames="N",paramnames=c("r","phi","K","N.0","sigma")) + +options(op) +``` + +### General rules + +1. C snippets must be valid C. They will embedded verbatim in a template file which will then be compiled by a call to `R CMD SHLIB`. If the resulting file does not compile, an error message wil be generated. No attempt is made by `pomp` to interpret this message. Typically, compilation errors are due to either the snippet's being invalid C or one or more undeclared variables. +1. Each state variable or parameter must be left undeclared in the snippet and declared in the corresponding argument to `pomp`, i.e., in either `statenames` or `paramnames`. Compiler errors that complain about undeclared state variables or parameters are likely due to failure to include these parameters in the appropriate vector of names. +1. Names of observables are determined by their names in the data. They must be referred to in measurement model snippets (rmeasure or dmeasure) by those names. +1. If the `pomp` object contains a table of covariates (see `?pomp`), then the variables in the covariate table will be available by their names in the context within which the snippet is executed. +1. `R` variables with names containing dots are replaced in the C codes by variable names in which all dots have been replaced by underscores ("_"). +1. A C snippet can declare local variables. Be careful not to use names that match those of state variables, observables, or parameters. The latter must never be declared within a snippet. +1. The header `R.h`, provided with `R`, will be included, making all of the [`R` C API](http://cran.r-project.org/doc/manuals/r-release/R-exts.html#The-R-API) available for use in the snippet. +1. The header `pomp.h`, provided with `pomp`, will be included, making all of the `pomp` C API available for use in every snippet. Do `file.show(system.file("include/pomp.h",package="pomp"))` to view this header file. +1. Snippets of C code passed to the `globals` argument of `pomp` will be included at the head of the generated C file. This can be used to define global variables, define useful functions, and include header files. + +### C snippets implementing Euler steps for use by `euler.sim` + +1. The ultimate goal of such a snippet is to replace the state variables with their new random values at the end of the time interval. Accordingly, each state variable should be over-written with its new value. +1. In addition to the states, parameters, covariates (if any), and observables, the variables `t` and `dt`, containing respectively the time at the beginning of the Euler step and the Euler step's duration, will be defined in the context in which the snippet is executed. + +### C snippets implementing the rmeasure component + +1. The ultimate goal of such a snippet is to fill the observables with random values drawn from the measurement model distribution. Accordingly, each observable should be assigned a new value. +1. In addition to the states, parameters, covariates (if any), and observables, the variable `t`, containing the time of the observation, will be defined in the context in which the snippet is executed. + +### C snippets implementing the dmeasure component + +1. The ultimate goal of such a snippet is to fill the `lik` variable with the likelihood of the data given the state. Alternatively, if `give_log=1`, `lik` should be filled with the log likelihood. +1. In addition to the states, parameters, covariates (if any), and observables, the variable `t`, containing the time of the observation, will be defined in the context in which the snippet is executed. + +### C snippets implementing the deterministic skeleton + +1. For each state variable, there is a corresponding component of the deterministic skeleton. The goal of such a snippet is to compute all the components. +1. When the skeleton is a map, the component corresponding to state variable `x` is named `Dx` and is the new value of `x` after one iteration of the map. +1. When the skeleton is a vectorfield, the component corresponding to state variable `x` is named `Dx` and is the value of $dx/dt$. +1. As with the other C snippets, all states, parameters and covariates, as well as the current time, `t`, will be defined in the context within which the snippet is executed. + +### C snippets implementing parameter transformations + +1. The parameter transformation taking a parameter vector from the scale defined by the model codes to another scale is specified as the `parameter.inv.transform` whilst the transformation taking a parameter vector from the alternative scale to that on which the model is defined is specified as the `parameter.transform`. +1. The goal of a either of these snippets is the computation of the values of the transformed parameters. The value of transformed parameter `x` should be assigned to variable `Tx`. +1. Time- and covariate-dependent transformations are not allowed. Therefore, the variables `t` and any covariates will not be available in the context within which a parameter transformation snippet is executed. + +## References + [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1120 From noreply at r-forge.r-project.org Sun Mar 1 16:17:09 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Sun, 1 Mar 2015 16:17:09 +0100 (CET) Subject: [Pomp-commits] r1121 - pkg/pomp pkg/pomp/man www/content www/vignettes Message-ID: <20150301151709.5AD1C18731C@r-forge.r-project.org> Author: kingaa Date: 2015-03-01 16:17:08 +0100 (Sun, 01 Mar 2015) New Revision: 1121 Modified: pkg/pomp/DESCRIPTION pkg/pomp/man/csnippet.Rd www/content/vignettes.htm www/vignettes/getting_started.R www/vignettes/getting_started.Rmd www/vignettes/getting_started.html www/vignettes/pomp.pdf Log: - improve Csnippet help page - simplify the Getting Started vignette - update the package vignettes webpage (remove intro and advanced topics vignettes) Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-01 03:41:09 UTC (rev 1120) +++ pkg/pomp/DESCRIPTION 2015-03-01 15:17:08 UTC (rev 1121) @@ -1,8 +1,8 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.62-2 -Date: 2015-02-28 +Version: 0.62-3 +Date: 2015-03-01 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), person(given=c("Edward","L."),family="Ionides",role=c("aut")), @@ -25,18 +25,18 @@ MailingList: Subscribe to pomp-announce at r-forge.r-project.org for announcements by going to http://lists.r-forge.r-project.org/mailman/listinfo/pomp-announce. Collate: aaa.R authors.R generics.R eulermultinom.R csnippet.R pomp-fun.R plugins.R builder.R - parmat.R logmeanexp.R slice-design.R + parmat.R logmeanexp.R slice-design.R profile-design.R sobol.R bsplines.R sannbox.R - pomp-class.R load.R pomp.R pomp-methods.R - rmeasure-pomp.R rprocess-pomp.R init-state-pomp.R - dmeasure-pomp.R dprocess-pomp.R skeleton-pomp.R + pomp-class.R load.R pomp.R pomp-methods.R + rmeasure-pomp.R rprocess-pomp.R init-state-pomp.R + dmeasure-pomp.R dprocess-pomp.R skeleton-pomp.R dprior-pomp.R rprior-pomp.R - simulate-pomp.R trajectory-pomp.R plot-pomp.R - pfilter.R pfilter-methods.R minim.R traj-match.R + simulate-pomp.R trajectory-pomp.R plot-pomp.R + pfilter.R pfilter-methods.R minim.R traj-match.R bsmc.R bsmc2.R mif.R mif-methods.R proposals.R pmcmc.R pmcmc-methods.R - nlf-funcs.R nlf-guts.R nlf-objfun.R nlf.R + nlf-funcs.R nlf-guts.R nlf-objfun.R nlf.R probe.R probe-match.R basic-probes.R spect.R spect-match.R abc.R abc-methods.R example.R Modified: pkg/pomp/man/csnippet.Rd =================================================================== --- pkg/pomp/man/csnippet.Rd 2015-03-01 03:41:09 UTC (rev 1120) +++ pkg/pomp/man/csnippet.Rd 2015-03-01 15:17:08 UTC (rev 1121) @@ -6,7 +6,7 @@ For including snippets of C code in \code{pomp} objects. } \usage{ - Csnippet(text); + Csnippet(text) } \arguments{ \item{text}{ @@ -18,12 +18,68 @@ } \section{Using C snippets to accelerate computations}{ From version 0.50, \pkg{pomp} provides a facility whereby users can define their model's components using inline C code. - The \code{pomp} constructor combines these \code{Csnippet}s into a compilable C file stored in the \R session's temporary directory. - They are then compiled (via \code{\link[=SHLIB]{R CMD SHLIB}}) into dynamically loadable shared objects. - This is then dynamically loaded as needed. + Furnishing one or more \code{Csnippet}s as arguments to the \code{pomp} constructor causes them to be written to a C file stored in the \R session's temporary directory, which is then compiled (via \code{\link[=SHLIB]{R CMD SHLIB}}) into a dynamically loadable shared object file. + This is then loaded as needed. - Instructions for writing models using \code{Csnippet}s, along with examples, are given in the tutorials on the \href{http://pomp.r-forge.r-project.org}{package website}. + \strong{Note to Windows and Mac users:} + By default, your \R installation may not support \code{\link[=SHLIB]{R CMD SHLIB}}. + Have a look at the tutorials on the package website for instructions on enabling this powerful feature of \R. + + In writing a \code{Csnippet} one must bear in mind both the \emph{goal} of the snippet, i.e., what computation it is intended to perform, and the \emph{context} in which it will be executed. + Details of both of these are given below in the form of rules governing the use of \code{Csnippet}s. + Illustrative examples are given in the tutorials on the \href{http://pomp.r-forge.r-project.org}{package website}. } +\section{General rules for writing C snippets}{ + \enumerate{ + \item C snippets must be valid C. They will embedded verbatim in a template file which will then be compiled by a call to \code{R CMD SHLIB}. If the resulting file does not compile, an error message wil be generated. No attempt is made by \pkg{pomp} to interpret this message. Typically, compilation errors are due to either invalid C syntax or undeclared variables. + \item State variables, parameters, observables, and covariates must be left undeclared in the snippet. State variables and parameters must be declared in either the \code{statenames} or \code{paramnames} argument to \code{pomp}, as appropriate. Compiler errors that complain about undeclared state variables or parameters are usually due to failure to include these parameters in the appropriate vector of names. + \item A C snippet can declare local variables. Be careful not to use names that match those of state variables, observables, or parameters. The latter must never be declared within a snippet. + \item Names of observables are determined by their names in the data. They must be referred to in measurement model snippets (rmeasure or dmeasure) by those names. + \item If the \code{pomp} object contains a table of covariates (see \code{\link{pomp}}), then the variables in the covariate table will be available, by their names, in the context within which the snippet is executed. + \item \R variables with names containing dots (\sQuote{.}) are replaced in the C codes by variable names in which all dots have been replaced by underscores (\sQuote{_}). + \item The header \file{R.h}, provided with \R, will be included in the generated C file, making all of the \href{http://cran.r-project.org/doc/manuals/r-release/R-exts.html#The-R-API}{\R C API} available for use in the snippet. + \item The header \file{pomp.h}, provided with \pkg{pomp}, will also be included, making all of the \pkg{pomp} C API available for use in every snippet. Do \preformatted{file.show(system.file("include/pomp.h",package="pomp"))} to view this header file. + \item Snippets of C code passed to the \code{globals} argument of \code{pomp} will be included at the head of the generated C file. This can be used to declare global variables, define useful functions, and include arbitrary header files. + } +} +\section{Rules for writing \code{rmeasure} snippets}{ + \enumerate{ + \item The goal of such a snippet is to fill the observables with random values drawn from the measurement model distribution. Accordingly, each observable should be assigned a new value. + \item In addition to the states, parameters, covariates (if any), and observables, the variable \code{t}, containing the time of the observation, will be defined in the context in which the snippet is executed. + } +} +\section{Rules for writing \code{dmeasure} snippets}{ + \enumerate{ + \item The goal of such a snippet is to fill the \code{lik} variable with the likelihood of the data given the state. Alternatively, if \code{give_log=1}, \code{lik} should be filled with the log likelihood. + \item In addition to the states, parameters, covariates (if any), and observables, the variable \code{t}, containing the time of the observation, will be defined in the context in which the snippet is executed. + } +} +\section{Rules for writing \code{euler.sim} and \code{discrete.time.sim} snippets}{ + \enumerate{ + \item The goal of such a snippet is to replace the state variables with their new random values at the end of the time interval. Accordingly, each state variable should be over-written with its new value. + \item In addition to the states, parameters, covariates (if any), and observables, the variables \code{t} and \code{dt}, containing respectively the time at the beginning of the Euler step and the Euler step's duration, will be defined in the context in which the snippet is executed. + } +} +\section{Rules for writing \code{skeleton} snippets}{ + \enumerate{ + \item For each state variable, there is a corresponding component of the deterministic skeleton. The goal of such a snippet is to compute all the components. + \item When the skeleton is a map, the component corresponding to state variable \code{x} is named \code{Dx} and is the new value of \code{x} after one iteration of the map. + \item When the skeleton is a vectorfield, the component corresponding to state variable \code{x} is named \code{Dx} and is the value of $dx/dt$. + \item As with the other C snippets, all states, parameters and covariates, as well as the current time, \code{t}, will be defined in the context within which the snippet is executed. + } +} +\section{Rules for writing parameter transformation snippets}{ + \enumerate{ + \item The parameter transformation mapping a parameter vector from the scale defined by the model codes to another scale is specified as the \code{parameter.inv.transform} whilst the transformation mapping a parameter vector from the alternative scale to that on which the model is defined is specified as the \code{parameter.transform}. + \item The goal of a these snippets is the computation of the values of the transformed parameters. The value of transformed parameter \code{x} should be assigned to variable \code{Tx}. + \item Time-, state-, and covariate-dependent transformations are not allowed. Therefore, neither the time, nor any state variables, nor any of the covariates will be available in the context within which a parameter transformation snippet is executed. + } +} +\section{Viewing the generated C code}{ + It can be useful to view the C code generated by calling \code{pomp} with one or more \code{Csnippet} arguments. + To do so, set \code{options(verbose=TRUE)} before calling \code{pomp}. + A message giving the name of the generated C file (in the session temporary directory) will be printed. +} \author{Aaron A. King \email{kingaa at umich dot edu}} \seealso{ \code{\link{pomp}}, \code{\link{plugins}}, and the tutorials on the \href{http://pomp.r-forge.r-project.org}{package website}. Modified: www/content/vignettes.htm =================================================================== --- www/content/vignettes.htm 2015-03-01 03:41:09 UTC (rev 1120) +++ www/content/vignettes.htm 2015-03-01 15:17:08 UTC (rev 1121) @@ -2,16 +2,10 @@ - - - + + + - - - - - - Modified: www/vignettes/getting_started.R =================================================================== --- www/vignettes/getting_started.R 2015-03-01 03:41:09 UTC (rev 1120) +++ www/vignettes/getting_started.R 2015-03-01 15:17:08 UTC (rev 1121) @@ -33,7 +33,7 @@ require(magrittr) require(pomp) theme_set(theme_bw()) -stopifnot(packageVersion("pomp")>="0.62-1") +stopifnot(packageVersion("pomp")>="0.62-2") options( keep.source=TRUE, stringsAsFactors=FALSE, @@ -205,11 +205,3 @@ coef(parus,transform=TRUE) <- partrans(parus,p,dir="inv") stopifnot(all.equal(p,coef(parus))) -## ----tempfile-view,eval=FALSE-------------------------------------------- -## op <- options(verbose=TRUE) -## -## parus <- pomp(data=parus.dat,times="year",t0=1959,rprocess=euler.sim(step.fun,delta.t=1/365), -## dmeasure=dmeas,rmeasure=rmeas,statenames="N",paramnames=c("r","phi","K","N.0","sigma")) -## -## options(op) - Modified: www/vignettes/getting_started.Rmd =================================================================== --- www/vignettes/getting_started.Rmd 2015-03-01 03:41:09 UTC (rev 1120) +++ www/vignettes/getting_started.Rmd 2015-03-01 15:17:08 UTC (rev 1121) @@ -1,7 +1,6 @@ --- title: "Getting started with pomp" author: "Aaron A. King" -date: "02/28/2015" output: html_document: theme: flatly @@ -14,6 +13,8 @@ Please share and remix noncommercially, mentioning its origin. ![CC-BY_NC](http://pomp.r-forge.r-project.org/graphics/cc-by-nc.png) +This document compiled with `pomp` version `r packageVersion("pomp")`. + ```{r opts,include=FALSE} library(knitr) prefix <- "getting-started" @@ -51,7 +52,7 @@ require(magrittr) require(pomp) theme_set(theme_bw()) -stopifnot(packageVersion("pomp")>="0.62-1") +stopifnot(packageVersion("pomp")>="0.62-2") options( keep.source=TRUE, stringsAsFactors=FALSE, @@ -229,7 +230,7 @@ The `rnorm` function is part of the [`R` API](http://cran.r-project.org/doc/manuals/r-release/R-exts.html#The-R-API): see the [manual on "Writing R Extensions"](http://cran.r-project.org/doc/manuals/r-release/R-exts.html) for a description of this and the other [distribution functions provided as part of the `R` API](http://cran.r-project.org/doc/manuals/r-release/R-exts.html#Distribution-functions). Finally, note that the state variable `N` is over-written by this snippet: it's value when the first line is executed is overwritten by the second line. -[A full set of rules for writing `pomp` C snippets is given below][rules]. +A full set of rules for writing `pomp` C snippets is given in the package help `?Csnippet`. With the process model in place, we can simulate the process model using the `simulate` function and plot several realizations for a given set of parameters. @@ -328,7 +329,7 @@ parus <- pomp(parus,skeleton=skel,skeleton.type="vectorfield",statenames="N",paramnames=c("r","K")) ``` Note that in this snippet, `DN` is filled with the value of the time-derivative of `N`. -[See below for a complete set of rules for writing C snippets for `pomp`][rules]. +See the package help (`?Csnippet`) for a complete set of rules for writing C snippets. With the deterministic skeleton in place we can generate several trajectories of the skeleton using `trajectory`, as follows, and plot the result. ```{r logistic-traj1} @@ -403,59 +404,4 @@ stopifnot(all.equal(p,coef(parus))) ``` -## Rules for writing C snippets - -To fully understand how `pomp` makes use of C snippets, it is informative to have a look at the C file created by any call to `pomp` involving one or more C snippets. -Run the following in an `R` session and view the C file that is created in the session's temporary directory. -```{r tempfile-view,eval=FALSE} -op <- options(verbose=TRUE) - -parus <- pomp(data=parus.dat,times="year",t0=1959,rprocess=euler.sim(step.fun,delta.t=1/365), - dmeasure=dmeas,rmeasure=rmeas,statenames="N",paramnames=c("r","phi","K","N.0","sigma")) - -options(op) -``` - -### General rules - -1. C snippets must be valid C. They will embedded verbatim in a template file which will then be compiled by a call to `R CMD SHLIB`. If the resulting file does not compile, an error message wil be generated. No attempt is made by `pomp` to interpret this message. Typically, compilation errors are due to either the snippet's being invalid C or one or more undeclared variables. -1. Each state variable or parameter must be left undeclared in the snippet and declared in the corresponding argument to `pomp`, i.e., in either `statenames` or `paramnames`. Compiler errors that complain about undeclared state variables or parameters are likely due to failure to include these parameters in the appropriate vector of names. -1. Names of observables are determined by their names in the data. They must be referred to in measurement model snippets (rmeasure or dmeasure) by those names. -1. If the `pomp` object contains a table of covariates (see `?pomp`), then the variables in the covariate table will be available by their names in the context within which the snippet is executed. -1. `R` variables with names containing dots are replaced in the C codes by variable names in which all dots have been replaced by underscores ("_"). -1. A C snippet can declare local variables. Be careful not to use names that match those of state variables, observables, or parameters. The latter must never be declared within a snippet. -1. The header `R.h`, provided with `R`, will be included, making all of the [`R` C API](http://cran.r-project.org/doc/manuals/r-release/R-exts.html#The-R-API) available for use in the snippet. -1. The header `pomp.h`, provided with `pomp`, will be included, making all of the `pomp` C API available for use in every snippet. Do `file.show(system.file("include/pomp.h",package="pomp"))` to view this header file. -1. Snippets of C code passed to the `globals` argument of `pomp` will be included at the head of the generated C file. This can be used to define global variables, define useful functions, and include header files. - -### C snippets implementing Euler steps for use by `euler.sim` - -1. The ultimate goal of such a snippet is to replace the state variables with their new random values at the end of the time interval. Accordingly, each state variable should be over-written with its new value. -1. In addition to the states, parameters, covariates (if any), and observables, the variables `t` and `dt`, containing respectively the time at the beginning of the Euler step and the Euler step's duration, will be defined in the context in which the snippet is executed. - -### C snippets implementing the rmeasure component - -1. The ultimate goal of such a snippet is to fill the observables with random values drawn from the measurement model distribution. Accordingly, each observable should be assigned a new value. -1. In addition to the states, parameters, covariates (if any), and observables, the variable `t`, containing the time of the observation, will be defined in the context in which the snippet is executed. - -### C snippets implementing the dmeasure component - -1. The ultimate goal of such a snippet is to fill the `lik` variable with the likelihood of the data given the state. Alternatively, if `give_log=1`, `lik` should be filled with the log likelihood. -1. In addition to the states, parameters, covariates (if any), and observables, the variable `t`, containing the time of the observation, will be defined in the context in which the snippet is executed. - -### C snippets implementing the deterministic skeleton - -1. For each state variable, there is a corresponding component of the deterministic skeleton. The goal of such a snippet is to compute all the components. -1. When the skeleton is a map, the component corresponding to state variable `x` is named `Dx` and is the new value of `x` after one iteration of the map. -1. When the skeleton is a vectorfield, the component corresponding to state variable `x` is named `Dx` and is the value of $dx/dt$. -1. As with the other C snippets, all states, parameters and covariates, as well as the current time, `t`, will be defined in the context within which the snippet is executed. - -### C snippets implementing parameter transformations - -1. The parameter transformation taking a parameter vector from the scale defined by the model codes to another scale is specified as the `parameter.inv.transform` whilst the transformation taking a parameter vector from the alternative scale to that on which the model is defined is specified as the `parameter.transform`. -1. The goal of a either of these snippets is the computation of the values of the transformed parameters. The value of transformed parameter `x` should be assigned to variable `Tx`. -1. Time- and covariate-dependent transformations are not allowed. Therefore, the variables `t` and any covariates will not be available in the context within which a parameter transformation snippet is executed. - ## References - -[rules]:./getting_started.html##rules-for-writing-c-snippets "Rules for writing C snippets" Modified: www/vignettes/getting_started.html =================================================================== --- www/vignettes/getting_started.html 2015-03-01 03:41:09 UTC (rev 1120) +++ www/vignettes/getting_started.html 2015-03-01 15:17:08 UTC (rev 1121) @@ -10,7 +10,6 @@ -Getting started with pomp @@ -64,7 +63,6 @@

Licensed under the Creative Commons attribution-noncommercial license. Please share and remix noncommercially, mentioning its origin.
CC-BY_NC

+

This document compiled with pomp version 0.62.2.

Partially observed Markov process (POMP) models

As its name implies pomp is focused on partially observed Markov process models. These are also known as state-space model, hidden Markov models, and stochastic dynamical systems models. Such models consist of an unobserved stochastic state process, connected to the data via an explicit model of the observation process. We refer to the former as the process model and the latter as the measurement model. Each model is, in fact, a probability distribution. If we let \(Y_t\) denote the measurement process at time \(t\) and \(X_t\) the state process, then by definition, the process model is determined by the density \(f_{X_t|X_{t-1}}\) and the measurement process by the density \(f_{Y_t|X_t}\). We think of the data, \(y^*_t\), \(t=1,\dots,T\) as being a single realization of the \(Y\) process. To implement a POMP model in pomp, we have to specify the measurement and process distributions.

@@ -108,18 +99,20 @@
+ + [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1121 From noreply at r-forge.r-project.org Sun Mar 1 17:21:55 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Sun, 1 Mar 2015 17:21:55 +0100 (CET) Subject: [Pomp-commits] r1122 - www/graphics Message-ID: <20150301162155.5A11B187270@r-forge.r-project.org> Author: kingaa Date: 2015-03-01 17:21:55 +0100 (Sun, 01 Mar 2015) New Revision: 1122 Added: www/graphics/pomp_schematic1.png www/graphics/pomp_schematic2.png Removed: www/graphics/state_space_diagram1.png www/graphics/state_space_diagram2.png Log: - change figures Added: www/graphics/pomp_schematic1.png =================================================================== --- www/graphics/pomp_schematic1.png (rev 0) +++ www/graphics/pomp_schematic1.png 2015-03-01 16:21:55 UTC (rev 1122) @@ -0,0 +1,371 @@ +?PNG + + +IHDR?1???TsRGB???bKGD??????? pHYs  ??tIME?:t0IG IDATx???$E???O?Yr%?d? ??"?EEqEAPQPD at 2 +HT?H??K?9??{??Y??v???tOw????8?#SPrb???????~iv??c??8=l??:Yo???tS?Z??PTg?*[??JWp.???}!????M???$?_? 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LN?????@C??]????7???I@'?#?>??????MJ?p??v?Z??2q??@K4?}"??IO?i)?-?? +??????F?????u?8]t2?????d +?>??@?!?? [w ?C??!}&??MP??Cx?V+u???f???x??H at 7(?@?A?}???????`^???m??7???mh??:???????u????Q?Z???H??fQdk???; ????z?!j?iUB?@??jw??_???c??rJ at OP^????F????k]?P??? +G?????c? +;?FC??m???'? E?n??K?@??????t@??+?A?`UOWjjeIT4[???@????G???@????O?H??t? ?+???DZ???4?0??4??4?e{7LX=?8?t????t2??`,o?????>b?u???UG'?!??:??r?? ^SG:Y?j>X???????t????????H+#?.?ga???Ge??Q???F??I?)???0????E?c:??VO?????*??[????k&?A:X???;???4?{#??Y??L ?j???{xm?????S4s[jw?&`&P???UQ??=?L?^????j?^???? t?@xd=??+ua2??];????x=??2?3w?L?g??Hu ?????O??k??BzQ??????`Q?q?? ????uvUO?????9E6??4?S?W?????L???c|??u?.???@?LS?2???f&`?!?#???F??s8?????i?E??t?M?'?E? ??@4%??mJ??F?*?-?l&`&???2????:0^?~?:e??????e??????(????\~l?? ?????? ?t?^ ??^$=?????8???Ndz????4??J%??3y'????????|???u?<]? ?@?t?]?u?A?? |?>F?#?u3P/??I?3??d?%=b?? +????/??(M??y??Sg?Z?? +?S?r?Y?4????TNw?+?p??+?'YW'>?*?tR?V!_????6t?tp?????p{&`&`&?k?u??t2,gx?&??????d??????5?T???Ojr??}?M??z??q?Rf=??4k??,?????? ?? ?? ?? $$gKOH?W?=??0????V???[?J?2?>?fA?????R??uT????3?K?/??\Gu??-?cm [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1122 From noreply at r-forge.r-project.org Sun Mar 1 17:38:26 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Sun, 1 Mar 2015 17:38:26 +0100 (CET) Subject: [Pomp-commits] r1123 - in www: graphics vignettes Message-ID: <20150301163826.D25671858F3@r-forge.r-project.org> Author: kingaa Date: 2015-03-01 17:38:26 +0100 (Sun, 01 Mar 2015) New Revision: 1123 Modified: www/graphics/pomp_schematic1.png www/graphics/pomp_schematic2.png www/vignettes/getting_started.Rmd www/vignettes/getting_started.html Log: - improve figures Modified: www/graphics/pomp_schematic1.png =================================================================== --- www/graphics/pomp_schematic1.png 2015-03-01 16:21:55 UTC (rev 1122) +++ www/graphics/pomp_schematic1.png 2015-03-01 16:38:26 UTC (rev 1123) @@ -1,371 +1,267 @@ ?PNG  -IHDR?1???TsRGB???bKGD??????? pHYs  ??tIME?:t0IG IDATx???$E???O?Yr%?d? ??"?EEqEAPQPD at 2 -HT?H??K?9??{??Y??v???tOw????8?#SPrb???????~iv??c??8=l??:Yo???tS?Z??PTg?*[??JWp.???}!????M???$?_? 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[TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1123 From noreply at r-forge.r-project.org Sun Mar 1 17:53:04 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Sun, 1 Mar 2015 17:53:04 +0100 (CET) Subject: [Pomp-commits] r1124 - / www/vignettes Message-ID: <20150301165305.0908F18754A@r-forge.r-project.org> Author: kingaa Date: 2015-03-01 17:53:04 +0100 (Sun, 01 Mar 2015) New Revision: 1124 Removed: trigger_build Modified: www/vignettes/getting_started.R www/vignettes/getting_started.Rmd www/vignettes/getting_started.html Log: - another small tweak Deleted: trigger_build =================================================================== Modified: www/vignettes/getting_started.R =================================================================== --- www/vignettes/getting_started.R 2015-03-01 16:38:26 UTC (rev 1123) +++ www/vignettes/getting_started.R 2015-03-01 16:53:04 UTC (rev 1124) @@ -94,7 +94,7 @@ step.fun <- Csnippet(" double dW = rnorm(0,sqrt(dt)); N += r*N*(1-N/K)*dt+sigma*N*dW; - ") +") ## ----logistic-pomp1,cache=FALSE------------------------------------------ parus <- pomp(data=parus.dat,time="year",t0=1959, @@ -114,7 +114,7 @@ ## ----logistic-rmeasure--------------------------------------------------- rmeas <- Csnippet(" pop = rpois(phi*N); - ") +") ## ----logistic-pomp2,cache=FALSE------------------------------------------ parus <- pomp(parus,rmeasure=rmeas,paramnames="phi",statenames="N") @@ -139,7 +139,7 @@ ## ----logistic-dmeasure--------------------------------------------------- dmeas <- Csnippet(" lik = dpois(pop,phi*N,give_log); - ") +") ## ----logistic-pomp3,cache=FALSE------------------------------------------ parus <- pomp(parus,dmeasure=dmeas,paramnames="phi",statenames="N") @@ -151,7 +151,7 @@ ## ----logistic-skeleton,cache=FALSE--------------------------------------- skel <- Csnippet(" DN = r*N*(1-N/K); - ") +") parus <- pomp(parus,skeleton=skel,skeleton.type="vectorfield",statenames="N",paramnames=c("r","K")) @@ -170,12 +170,12 @@ bh.step <- Csnippet(" double eps = rlnorm(-sigma*sigma/2,sigma); N = a*N/(1+b*N)*eps; - ") +") ## ----bh-skeleton--------------------------------------------------------- bh.skel <- Csnippet(" DN = a*N/(1+b*N); - ") +") ## ----bh-pomp1,cache=FALSE------------------------------------------------ parus.bh <- pomp(parus,rprocess=discrete.time.sim(bh.step,delta.t=1),skeleton=bh.skel,skeleton.type="map",skelmap.delta.t=1,statenames="N",paramnames=c("a","b","sigma")) @@ -190,12 +190,12 @@ partrans <- Csnippet(" Tr = exp(r); TK = exp(K); - ") +") parinvtrans <- Csnippet(" Tr = log(r); TK = log(K); - ") +") parus <- pomp(parus,parameter.transform=partrans,parameter.inv.transform=parinvtrans, paramnames=c("r","K")) Modified: www/vignettes/getting_started.Rmd =================================================================== --- www/vignettes/getting_started.Rmd 2015-03-01 16:38:26 UTC (rev 1123) +++ www/vignettes/getting_started.Rmd 2015-03-01 16:53:04 UTC (rev 1124) @@ -83,18 +83,21 @@ We will illustrate this using some simple examples. ----------------------------------- -![schematic1](../graphics/pomp_schematic1.png) -Schematic of the structure of a POMP showing causal relations and direction of information flow. +The following is a schematic of the structure of a POMP showing causal relations between the process model, the measurement model, and the data. **The key perspective to keep in mind is that the model is to be viewed as the process that generated the data.** +![schematic1](../graphics/pomp_schematic1.png) + ----------------------------------- + +Here is another POMP model schematic, showing dependence among model variables. + ![schematic2](../graphics/pomp_schematic2.png) -Another POMP model schematic, showing dependence among model variables. -State variables, $x$, at time $t$ depend only on state variables at the previous timestep. -Measurements, $y$, at time $t$ depend only on the state at that time. -Formally, $\mathrm{Prob}[X_t|X_1,\dots,X_{t-1},Y_1,\dots,Y_{t-1}]=\mathrm{Prob}[X_t|X_{t-1}]$ and $\mathrm{Prob}[Y_t|X_1,\dots,X_{t},Y_1,\dots,Y_{t-1}]=\mathrm{Prob}[Y_t|X_{t}]$ for all $t=1,\dots,T$. +State variables, $X$, at time $t$ depend only on state variables at the previous timestep. +Measurements, $Y$, at time $t$ depend only on the state at that time. +Formally, $$\mathrm{Prob}[X_t|X_0,\dots,X_{t-1},Y_1,\dots,Y_{t-1}]=\mathrm{Prob}[X_t|X_{t-1}]$$ and $$\mathrm{Prob}[Y_t|X_0,\dots,X_{t},Y_1,\dots,Y_{t-1}]=\mathrm{Prob}[Y_t|X_{t}],$$ for all $t=1,\dots,T$. ----------------------------------- @@ -209,7 +212,7 @@ step.fun <- Csnippet(" double dW = rnorm(0,sqrt(dt)); N += r*N*(1-N/K)*dt+sigma*N*dW; - ") +") ``` This is just a snippet of C code: not all the variables are declared and the context of the snippet is not specified. @@ -259,7 +262,7 @@ ```{r logistic-rmeasure} rmeas <- Csnippet(" pop = rpois(phi*N); - ") +") ``` In this snippet of code, `N` is the state variable, `phi` is another parameter, and `pop` is the name of our observable, as defined in the dataset `parus.dat`. The `rpois` function is part of the [`R` API](http://cran.r-project.org/doc/manuals/r-release/R-exts.html#The-R-API): it takes a single argument---the Poisson distribution's parameter---and returns a pseudo-random draw from the Poisson distribution with that parameter. @@ -295,7 +298,7 @@ ```{r logistic-dmeasure} dmeas <- Csnippet(" lik = dpois(pop,phi*N,give_log); - ") +") ``` and we fold it into the `pomp` object via ```{r logistic-pomp3,cache=FALSE} @@ -324,7 +327,7 @@ ```{r logistic-skeleton,cache=FALSE} skel <- Csnippet(" DN = r*N*(1-N/K); - ") +") parus <- pomp(parus,skeleton=skel,skeleton.type="vectorfield",statenames="N",paramnames=c("r","K")) ``` @@ -357,14 +360,14 @@ bh.step <- Csnippet(" double eps = rlnorm(-sigma*sigma/2,sigma); N = a*N/(1+b*N)*eps; - ") +") ``` A corresponding skeleton is the deterministic Beverton-Holt map obtained by setting $e_t=1$ in the above equation. A snippet that implements this map is ```{r bh-skeleton} bh.skel <- Csnippet(" DN = a*N/(1+b*N); - ") +") ``` Note that, as in the continuous case, we indicate the new value of the state variable by prepending `D` to the variable name. @@ -388,12 +391,12 @@ partrans <- Csnippet(" Tr = exp(r); TK = exp(K); - ") +") parinvtrans <- Csnippet(" Tr = log(r); TK = log(K); - ") +") parus <- pomp(parus,parameter.transform=partrans,parameter.inv.transform=parinvtrans, paramnames=c("r","K")) Modified: www/vignettes/getting_started.html =================================================================== --- www/vignettes/getting_started.html 2015-03-01 16:38:26 UTC (rev 1123) +++ www/vignettes/getting_started.html 2015-03-01 16:53:04 UTC (rev 1124) @@ -95,24 +95,14 @@
  • we might wish to evaluate the density itself at given values of \(X_t\) and/or \(Y_t\).

    • We refer to the simulation of \(f_{X_t|X_{t-1}}\) as the rprocess component of the POMP model, the evaluation of \(f_{X_t|X_{t-1}}\) as the dprocess component, the simulation of \(f_{Y_t|X_t}\), as the rmeasure component, and the evaluation of \(f_{Y_t|X_t}\) as the dmeasure component. Methods that make no use of the dprocess component are called ?plug-and-play? methods. At present, pomp is focused on such methods, so there is no reason to focus on the dprocess component any further. In the following, we will illustrate and explain how one specifies the rprocess, rmeasure, and dmeasure components of a model in pomp. We will illustrate this using some simple examples.

    -
    Introduction to pomp(PDF)(R code)Getting started with pomp(HTML)(R code)
    Advanced topics in pomp(PDF)(R code)
    pomp package manual (PDF)
    --- - - [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1124 From noreply at r-forge.r-project.org Mon Mar 2 00:55:22 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Mon, 2 Mar 2015 00:55:22 +0100 (CET) Subject: [Pomp-commits] r1125 - in pkg/pomp: . src tests Message-ID: <20150301235522.3B859186F2B@r-forge.r-project.org> Author: kingaa Date: 2015-03-02 00:55:21 +0100 (Mon, 02 Mar 2015) New Revision: 1125 Added: pkg/pomp/tests/getting_started.R pkg/pomp/tests/getting_started.Rout.save Modified: pkg/pomp/DESCRIPTION pkg/pomp/src/pomp_fun.c Log: - fix bug causing crashes in rstudio - add test of 'getting started' vignette's codes Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-01 16:53:04 UTC (rev 1124) +++ pkg/pomp/DESCRIPTION 2015-03-01 23:55:21 UTC (rev 1125) @@ -1,7 +1,7 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.62-3 +Version: 0.62-4 Date: 2015-03-01 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), Modified: pkg/pomp/src/pomp_fun.c =================================================================== --- pkg/pomp/src/pomp_fun.c 2015-03-01 16:53:04 UTC (rev 1124) +++ pkg/pomp/src/pomp_fun.c 2015-03-01 23:55:21 UTC (rev 1125) @@ -36,7 +36,7 @@ } switch (*mode) { - case native: + case native: { SEXP nsi; PROTECT(nsi = eval(lang3(install("getNativeSymbolInfo"),nf,pack),R_BaseEnv)); nprotect++; @@ -51,7 +51,7 @@ fname = (const char *) CHARACTER_DATA(STRING_ELT(nf,0)); pkg = (const char *) CHARACTER_DATA(STRING_ELT(pack,0)); ff = R_GetCCallable(pkg,fname); - PROTECT(f = R_MakeExternalPtr(ff,pfun,R_NilValue)); nprotect++; + PROTECT(f = R_MakeExternalPtr(ff,R_NilValue,R_NilValue)); nprotect++; } break; } Added: pkg/pomp/tests/getting_started.R =================================================================== --- pkg/pomp/tests/getting_started.R (rev 0) +++ pkg/pomp/tests/getting_started.R 2015-03-01 23:55:21 UTC (rev 1125) @@ -0,0 +1,125 @@ +require(pomp) + +options( + keep.source=TRUE, + stringsAsFactors=FALSE, + encoding="UTF-8" + ) + +parus.dat <- read.csv(text=" + year,pop + 1960,148 + 1961,258 + 1962,185 + 1963,170 + 1964,267 + 1965,239 + 1966,196 + 1967,132 + 1968,167 + 1969,186 + 1970,128 + 1971,227 + 1972,174 + 1973,177 + 1974,137 + 1975,172 + 1976,119 + 1977,226 + 1978,166 + 1979,161 + 1980,199 + 1981,306 + 1982,206 + 1983,350 + 1984,214 + 1985,175 + 1986,211" + ) + +## ----logistic-step-fun--------------------------------------------------- +step.fun <- Csnippet(" + double dW = rnorm(0,sqrt(dt)); + N += r*N*(1-N/K)*dt+sigma*N*dW; +") + +## ----logistic-pomp1,cache=FALSE------------------------------------------ +parus <- pomp(data=parus.dat,time="year",t0=1959, + rprocess=euler.sim(step.fun=step.fun,delta.t=1/365), + statenames="N",paramnames=c("r","K","sigma")) + +## ----logistic-simul1----------------------------------------------------- +simStates <- simulate(parus,nsim=10,params=c(r=0.2,K=200,sigma=0.5,N.0=200),states=TRUE) + +## ----logistic-rmeasure--------------------------------------------------- +rmeas <- Csnippet(" + pop = rpois(phi*N); +") + +## ----logistic-pomp2,cache=FALSE------------------------------------------ +parus <- pomp(parus,rmeasure=rmeas,paramnames="phi",statenames="N") + +## ----logistic-simul2----------------------------------------------------- +sim <- simulate(parus,params=c(r=0.2,K=200,phi=0.5,sigma=0.5,N.0=200), + nsim=10,obs=TRUE,states=TRUE) + +## ----logistic-dmeasure--------------------------------------------------- +dmeas <- Csnippet(" + lik = dpois(pop,phi*N,give_log); +") + +## ----logistic-pomp3,cache=FALSE------------------------------------------ +parus <- pomp(parus,dmeasure=dmeas,paramnames="phi",statenames="N") + +## ----logistic-pfilter---------------------------------------------------- +pf <- pfilter(parus,Np=1000,params=c(r=0.2,K=200,phi=0.5,sigma=0.5,N.0=200)) + +## ----logistic-skeleton,cache=FALSE--------------------------------------- +skel <- Csnippet(" + DN = r*N*(1-N/K); +") + +parus <- pomp(parus,skeleton=skel,skeleton.type="vectorfield",statenames="N",paramnames=c("r","K")) + +## ----logistic-traj1------------------------------------------------------ +pars <- parmat(c(r=1,K=200,phi=0.5,sigma=0.5,N.0=20),5) +pars["N.0",] <- seq(20,300,length=5) +traj <- trajectory(parus,params=pars,times=seq(1959,1970,by=0.01)) + +## ----bh-stepfun---------------------------------------------------------- +bh.step <- Csnippet(" + double eps = rlnorm(-sigma*sigma/2,sigma); + N = a*N/(1+b*N)*eps; +") + +## ----bh-skeleton--------------------------------------------------------- +bh.skel <- Csnippet(" + DN = a*N/(1+b*N); +") + +## ----bh-pomp1,cache=FALSE------------------------------------------------ +parus.bh <- pomp(parus,rprocess=discrete.time.sim(bh.step,delta.t=1),skeleton=bh.skel,skeleton.type="map",skelmap.delta.t=1,statenames="N",paramnames=c("a","b","sigma")) + +## ----bh-test------------------------------------------------------------- +coef(parus.bh) <- c(a=1.1,b=5e-4,sigma=0.5,N.0=30,phi=1) +sim <- simulate(parus.bh) +traj <- trajectory(parus.bh) +pf <- pfilter(parus.bh,Np=1000) + +## ----logistic-partrans,cache=FALSE--------------------------------------- +partrans <- Csnippet(" + Tr = exp(r); + TK = exp(K); +") + +parinvtrans <- Csnippet(" + Tr = log(r); + TK = log(K); +") + +parus <- pomp(parus,parameter.transform=partrans,parameter.inv.transform=parinvtrans,paramnames=c("r","K")) + +## ----logistic-partrans-test,include=FALSE,cache=FALSE-------------------- +p <- c(r=1,K=200,phi=1,N.0=200,sigma=0.5) +coef(parus,transform=TRUE) <- partrans(parus,p,dir="inv") +stopifnot(all.equal(p,coef(parus))) Added: pkg/pomp/tests/getting_started.Rout.save =================================================================== --- pkg/pomp/tests/getting_started.Rout.save (rev 0) +++ pkg/pomp/tests/getting_started.Rout.save 2015-03-01 23:55:21 UTC (rev 1125) @@ -0,0 +1,149 @@ + +R version 3.1.2 (2014-10-31) -- "Pumpkin Helmet" +Copyright (C) 2014 The R Foundation for Statistical Computing +Platform: x86_64-unknown-linux-gnu (64-bit) + +R is free software and comes with ABSOLUTELY NO WARRANTY. +You are welcome to redistribute it under certain conditions. +Type 'license()' or 'licence()' for distribution details. + +R is a collaborative project with many contributors. +Type 'contributors()' for more information and +'citation()' on how to cite R or R packages in publications. + +Type 'demo()' for some demos, 'help()' for on-line help, or +'help.start()' for an HTML browser interface to help. +Type 'q()' to quit R. + +> require(pomp) +Loading required package: pomp +Loading required package: subplex +Loading required package: nloptr +> +> options( ++ keep.source=TRUE, ++ stringsAsFactors=FALSE, ++ encoding="UTF-8" ++ ) +> +> parus.dat <- read.csv(text=" ++ year,pop ++ 1960,148 ++ 1961,258 ++ 1962,185 ++ 1963,170 ++ 1964,267 ++ 1965,239 ++ 1966,196 ++ 1967,132 ++ 1968,167 ++ 1969,186 ++ 1970,128 ++ 1971,227 ++ 1972,174 ++ 1973,177 ++ 1974,137 ++ 1975,172 ++ 1976,119 ++ 1977,226 ++ 1978,166 ++ 1979,161 ++ 1980,199 ++ 1981,306 ++ 1982,206 ++ 1983,350 ++ 1984,214 ++ 1985,175 ++ 1986,211" ++ ) +> +> ## ----logistic-step-fun--------------------------------------------------- +> step.fun <- Csnippet(" ++ double dW = rnorm(0,sqrt(dt)); ++ N += r*N*(1-N/K)*dt+sigma*N*dW; ++ ") +> +> ## ----logistic-pomp1,cache=FALSE------------------------------------------ +> parus <- pomp(data=parus.dat,time="year",t0=1959, ++ rprocess=euler.sim(step.fun=step.fun,delta.t=1/365), ++ statenames="N",paramnames=c("r","K","sigma")) +> +> ## ----logistic-simul1----------------------------------------------------- +> simStates <- simulate(parus,nsim=10,params=c(r=0.2,K=200,sigma=0.5,N.0=200),states=TRUE) +> +> ## ----logistic-rmeasure--------------------------------------------------- +> rmeas <- Csnippet(" ++ pop = rpois(phi*N); ++ ") +> +> ## ----logistic-pomp2,cache=FALSE------------------------------------------ +> parus <- pomp(parus,rmeasure=rmeas,paramnames="phi",statenames="N") +> +> ## ----logistic-simul2----------------------------------------------------- +> sim <- simulate(parus,params=c(r=0.2,K=200,phi=0.5,sigma=0.5,N.0=200), ++ nsim=10,obs=TRUE,states=TRUE) +> +> ## ----logistic-dmeasure--------------------------------------------------- +> dmeas <- Csnippet(" ++ lik = dpois(pop,phi*N,give_log); ++ ") +> +> ## ----logistic-pomp3,cache=FALSE------------------------------------------ +> parus <- pomp(parus,dmeasure=dmeas,paramnames="phi",statenames="N") +> +> ## ----logistic-pfilter---------------------------------------------------- +> pf <- pfilter(parus,Np=1000,params=c(r=0.2,K=200,phi=0.5,sigma=0.5,N.0=200)) +> +> ## ----logistic-skeleton,cache=FALSE--------------------------------------- +> skel <- Csnippet(" ++ DN = r*N*(1-N/K); ++ ") +> +> parus <- pomp(parus,skeleton=skel,skeleton.type="vectorfield",statenames="N",paramnames=c("r","K")) +> +> ## ----logistic-traj1------------------------------------------------------ +> pars <- parmat(c(r=1,K=200,phi=0.5,sigma=0.5,N.0=20),5) +> pars["N.0",] <- seq(20,300,length=5) +> traj <- trajectory(parus,params=pars,times=seq(1959,1970,by=0.01)) +> +> ## ----bh-stepfun---------------------------------------------------------- +> bh.step <- Csnippet(" ++ double eps = rlnorm(-sigma*sigma/2,sigma); ++ N = a*N/(1+b*N)*eps; ++ ") +> +> ## ----bh-skeleton--------------------------------------------------------- +> bh.skel <- Csnippet(" ++ DN = a*N/(1+b*N); ++ ") +> +> ## ----bh-pomp1,cache=FALSE------------------------------------------------ +> parus.bh <- pomp(parus,rprocess=discrete.time.sim(bh.step,delta.t=1),skeleton=bh.skel,skeleton.type="map",skelmap.delta.t=1,statenames="N",paramnames=c("a","b","sigma")) +> +> ## ----bh-test------------------------------------------------------------- +> coef(parus.bh) <- c(a=1.1,b=5e-4,sigma=0.5,N.0=30,phi=1) +> sim <- simulate(parus.bh) +> traj <- trajectory(parus.bh) +> pf <- pfilter(parus.bh,Np=1000) +> +> ## ----logistic-partrans,cache=FALSE--------------------------------------- +> partrans <- Csnippet(" ++ Tr = exp(r); ++ TK = exp(K); ++ ") +> +> parinvtrans <- Csnippet(" ++ Tr = log(r); ++ TK = log(K); ++ ") +> +> parus <- pomp(parus,parameter.transform=partrans,parameter.inv.transform=parinvtrans,paramnames=c("r","K")) +> +> ## ----logistic-partrans-test,include=FALSE,cache=FALSE-------------------- +> p <- c(r=1,K=200,phi=1,N.0=200,sigma=0.5) +> coef(parus,transform=TRUE) <- partrans(parus,p,dir="inv") +> stopifnot(all.equal(p,coef(parus))) +> +> proc.time() + user system elapsed + 2.321 0.465 2.752 From noreply at r-forge.r-project.org Mon Mar 2 02:25:09 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Mon, 2 Mar 2015 02:25:09 +0100 (CET) Subject: [Pomp-commits] r1126 - www/vignettes Message-ID: <20150302012509.11CD71867C1@r-forge.r-project.org> Author: kingaa Date: 2015-03-02 02:25:08 +0100 (Mon, 02 Mar 2015) New Revision: 1126 Modified: www/vignettes/getting_started.html Log: - updated Modified: www/vignettes/getting_started.html =================================================================== --- www/vignettes/getting_started.html 2015-03-01 23:55:21 UTC (rev 1125) +++ www/vignettes/getting_started.html 2015-03-02 01:25:08 UTC (rev 1126) @@ -85,7 +85,7 @@

    Licensed under the Creative Commons attribution-noncommercial license. Please share and remix noncommercially, mentioning its origin.
    CC-BY_NC

    -

    This document compiled with pomp version 0.62.2.

    +

    This document compiled with pomp version 0.62.4.

    Partially observed Markov process (POMP) models

    As its name implies pomp is focused on partially observed Markov process models. These are also known as state-space model, hidden Markov models, and stochastic dynamical systems models. Such models consist of an unobserved stochastic state process, connected to the data via an explicit model of the observation process. We refer to the former as the process model and the latter as the measurement model. Each model is, in fact, a probability distribution. If we let \(Y_t\) denote the measurement process at time \(t\) and \(X_t\) the state process, then by definition, the process model is determined by the density \(f_{X_t|X_{t-1}}\) and the measurement process by the density \(f_{Y_t|X_t}\). We think of the data, \(y^*_t\), \(t=1,\dots,T\) as being a single realization of the \(Y\) process. To implement a POMP model in pomp, we have to specify the measurement and process distributions.

    From noreply at r-forge.r-project.org Mon Mar 2 13:46:40 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Mon, 2 Mar 2015 13:46:40 +0100 (CET) Subject: [Pomp-commits] r1127 - pkg/pompExamples Message-ID: <20150302124640.B5B501875A7@r-forge.r-project.org> Author: kingaa Date: 2015-03-02 13:46:40 +0100 (Mon, 02 Mar 2015) New Revision: 1127 Modified: pkg/pompExamples/DESCRIPTION Log: - bump pompExamples to trigger rebuild Modified: pkg/pompExamples/DESCRIPTION =================================================================== --- pkg/pompExamples/DESCRIPTION 2015-03-02 01:25:08 UTC (rev 1126) +++ pkg/pompExamples/DESCRIPTION 2015-03-02 12:46:40 UTC (rev 1127) @@ -2,7 +2,7 @@ Type: Package Title: Additional pomp examples Version: 0.27-1 -Date: 2015-02-25 +Date: 2015-03-02 Maintainer: Aaron A. King Authors at R: c(person(given=c("Aaron","A."),family="King",role=c("aut","cre"), email="kingaa at umich.edu"), From noreply at r-forge.r-project.org Tue Mar 3 04:17:36 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Tue, 3 Mar 2015 04:17:36 +0100 (CET) Subject: [Pomp-commits] r1128 - in pkg/pomp: . man Message-ID: <20150303031736.9002C187810@r-forge.r-project.org> Author: kingaa Date: 2015-03-03 04:17:35 +0100 (Tue, 03 Mar 2015) New Revision: 1128 Modified: pkg/pomp/DESCRIPTION pkg/pomp/man/pomp.Rd Log: - add alias for accumulator variables Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-02 12:46:40 UTC (rev 1127) +++ pkg/pomp/DESCRIPTION 2015-03-03 03:17:35 UTC (rev 1128) @@ -1,8 +1,8 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.62-4 -Date: 2015-03-01 +Version: 0.62-5 +Date: 2015-03-02 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), person(given=c("Edward","L."),family="Ionides",role=c("aut")), Modified: pkg/pomp/man/pomp.Rd =================================================================== --- pkg/pomp/man/pomp.Rd 2015-03-02 12:46:40 UTC (rev 1127) +++ pkg/pomp/man/pomp.Rd 2015-03-03 03:17:35 UTC (rev 1128) @@ -11,6 +11,7 @@ \alias{pomp,pomp-method} \alias{pomp-pomp} \alias{pomp-class} +\alias{accumulator variables} \description{ This function constructs a \code{pomp} object, encoding a partially-observed Markov process model together with a uni- or multivariate time series. From noreply at r-forge.r-project.org Tue Mar 3 04:17:39 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Tue, 3 Mar 2015 04:17:39 +0100 (CET) Subject: [Pomp-commits] r1129 - www/vignettes Message-ID: <20150303031739.D5BEB187810@r-forge.r-project.org> Author: kingaa Date: 2015-03-03 04:17:39 +0100 (Tue, 03 Mar 2015) New Revision: 1129 Modified: www/vignettes/pomp.pdf Log: - add alias for accumulator variables Modified: www/vignettes/pomp.pdf =================================================================== (Binary files differ) From noreply at r-forge.r-project.org Wed Mar 4 14:09:14 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Wed, 4 Mar 2015 14:09:14 +0100 (CET) Subject: [Pomp-commits] r1130 - www/vignettes Message-ID: <20150304130914.AB04C18103A@r-forge.r-project.org> Author: kingaa Date: 2015-03-04 14:09:14 +0100 (Wed, 04 Mar 2015) New Revision: 1130 Removed: www/vignettes/bsmc-ricker-flat-prior.rda www/vignettes/bsmc-ricker-normal-prior.rda www/vignettes/gompertz-multi-mif.rda www/vignettes/gompertz-performance.rda www/vignettes/gompertz-pfilter-guess.rda www/vignettes/gompertz-trajmatch.rda www/vignettes/nlf-block-boot.rda www/vignettes/nlf-boot.rda www/vignettes/nlf-fit-from-truth.rda www/vignettes/nlf-fits.rda www/vignettes/nlf-lag-tests.rda www/vignettes/nlf-multi-short.rda www/vignettes/plugin-C-code.rda www/vignettes/plugin-R-code.rda www/vignettes/ricker-comparison.rda www/vignettes/ricker-first-probe.rda www/vignettes/ricker-mif.rda www/vignettes/ricker-probe-match.rda www/vignettes/ricker-probe.rda www/vignettes/vectorized-C-code.rda www/vignettes/vectorized-R-code.rda Modified: www/vignettes/Makefile Log: - remove all .rda files from intro and advanced vignettes Modified: www/vignettes/Makefile =================================================================== --- www/vignettes/Makefile 2015-03-03 03:17:39 UTC (rev 1129) +++ www/vignettes/Makefile 2015-03-04 13:09:14 UTC (rev 1130) @@ -7,7 +7,7 @@ default: vignettes clean -vignettes: intro_to_pomp.pdf intro_to_pomp.R getting_started.html getting_started.R +vignettes: getting_started.html getting_started.R %.R: %.Rnw $(RSCRIPT) -e 'library(knitr); purl("$*.Rnw")' Deleted: www/vignettes/bsmc-ricker-flat-prior.rda =================================================================== (Binary files differ) Deleted: www/vignettes/bsmc-ricker-normal-prior.rda =================================================================== (Binary files differ) Deleted: www/vignettes/gompertz-multi-mif.rda =================================================================== (Binary files differ) Deleted: www/vignettes/gompertz-performance.rda =================================================================== (Binary files differ) Deleted: www/vignettes/gompertz-pfilter-guess.rda =================================================================== (Binary files differ) Deleted: www/vignettes/gompertz-trajmatch.rda =================================================================== (Binary files differ) Deleted: www/vignettes/nlf-block-boot.rda =================================================================== (Binary files differ) Deleted: www/vignettes/nlf-boot.rda =================================================================== (Binary files differ) Deleted: www/vignettes/nlf-fit-from-truth.rda =================================================================== (Binary files differ) Deleted: www/vignettes/nlf-fits.rda =================================================================== (Binary files differ) Deleted: www/vignettes/nlf-lag-tests.rda =================================================================== (Binary files differ) Deleted: www/vignettes/nlf-multi-short.rda =================================================================== (Binary files differ) Deleted: www/vignettes/plugin-C-code.rda =================================================================== (Binary files differ) Deleted: www/vignettes/plugin-R-code.rda =================================================================== (Binary files differ) Deleted: www/vignettes/ricker-comparison.rda =================================================================== (Binary files differ) Deleted: www/vignettes/ricker-first-probe.rda =================================================================== (Binary files differ) Deleted: www/vignettes/ricker-mif.rda =================================================================== (Binary files differ) Deleted: www/vignettes/ricker-probe-match.rda =================================================================== (Binary files differ) Deleted: www/vignettes/ricker-probe.rda =================================================================== (Binary files differ) Deleted: www/vignettes/vectorized-C-code.rda =================================================================== (Binary files differ) Deleted: www/vignettes/vectorized-R-code.rda =================================================================== (Binary files differ) From noreply at r-forge.r-project.org Wed Mar 4 14:09:19 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Wed, 4 Mar 2015 14:09:19 +0100 (CET) Subject: [Pomp-commits] r1131 - pkg pkg/pomp/man www www/content www/help www/vignettes Message-ID: <20150304130919.F341318103A@r-forge.r-project.org> Author: kingaa Date: 2015-03-04 14:09:19 +0100 (Wed, 04 Mar 2015) New Revision: 1131 Added: www/help/ www/help/00Index.html www/help/00frame_toc.html www/help/LondonYorke.html www/help/Makefile www/help/R.css www/help/abc.html www/help/basic-probes.html www/help/blowflies.html www/help/bsmc.html www/help/bsplines.html www/help/builder.html www/help/csnippet.html www/help/dacca.html www/help/design.html www/help/eulermultinom.html www/help/example.html www/help/gompertz.html www/help/index.html www/help/logmeanexp.html www/help/lowlevel.html www/help/mif.html www/help/nlf.html www/help/ou2.html www/help/parmat.html www/help/particles-mif.html www/help/pfilter.html www/help/plugins.html www/help/pmcmc.html www/help/pomp-fun.html www/help/pomp-methods.html www/help/pomp-package.html www/help/pomp.html www/help/pomp.pdf www/help/probe.html www/help/proposals.html www/help/ricker.html www/help/rw2.html www/help/sannbox.html www/help/simulate-pomp.html www/help/sir.html www/help/spect.html www/help/traj-match.html Removed: www/vignettes/index.html www/vignettes/pomp.pdf Modified: pkg/Makefile pkg/pomp/man/example.Rd www/content/vignettes.htm www/index.php www/vignettes/Makefile Log: - add html version of manual to package website Modified: pkg/Makefile =================================================================== --- pkg/Makefile 2015-03-04 13:09:14 UTC (rev 1130) +++ pkg/Makefile 2015-03-04 13:09:19 UTC (rev 1131) @@ -32,12 +32,12 @@ %.dist %.manual %.vignettes: export R_QPDF=qpdf %.dist %.manual %.vignettes: export R_GSCMD=gs %.dist %.manual %.vignettes: export GS_QUALITY=ebook -%.dist %.manual %.vignettes: export R_HOME=$(shell $(REXE) RHOME) +%.dist %.manual %.vignettes %.help: export R_HOME=$(shell $(REXE) RHOME) %.check %.crancheck: export _R_CHECK_ALL_NON_ISO_C_=TRUE %.crancheck: export R_PROFILE_USER=./Rprofile %.check %.crancheck: export _R_CHECK_WALL_FORTRAN_=TRUE %.check %.xcheck: export POMP_FULL_TESTS=yes -%.vignettes %.data: export R_LIBS=$(CURDIR)/library +%.vignettes %.help %.data: export R_LIBS=$(CURDIR)/library %.bin %.check %.qcheck %.qqcheck %.xcheck %.crancheck %.upload %.publish %.clean %.install %.win: PKG = $*_$(shell perl -ne 'print $$1 if /Version:\s+(\d+\.\d+-\d+)/;' $*/DESCRIPTION) pomp.vignettes: pomp.install pomp.manual @@ -48,6 +48,9 @@ pompExamples.vignettes: pompExamples.install (cd pompExamples/vignettes; make) +pomp.help: pomp.install + (cd ../www/help; make) + %.data: %.install cd $*/inst/data-R; make Modified: pkg/pomp/man/example.Rd =================================================================== --- pkg/pomp/man/example.Rd 2015-03-04 13:09:14 UTC (rev 1130) +++ pkg/pomp/man/example.Rd 2015-03-04 13:09:19 UTC (rev 1131) @@ -40,8 +40,10 @@ pompExample(euler.sir) pompExample("gompertz") pompExample(ricker,envir=NULL) +\dontrun{ file.show(system.file("examples/bbs.R",package="pomp")) } +} \seealso{ \code{\link{blowflies}}, \code{\link{dacca}}, \code{\link{gompertz}}, \code{\link{ou2}}, \code{\link{ricker}}, \code{\link{rw2}}, Modified: www/content/vignettes.htm =================================================================== --- www/content/vignettes.htm 2015-03-04 13:09:14 UTC (rev 1130) +++ www/content/vignettes.htm 2015-03-04 13:09:19 UTC (rev 1131) @@ -7,6 +7,7 @@
    - + +
    (R code)
    pomp package manual(PDF)(HTML)(PDF)
    Added: www/help/00Index.html =================================================================== --- www/help/00Index.html (rev 0) +++ www/help/00Index.html 2015-03-04 13:09:19 UTC (rev 1131) @@ -0,0 +1,810 @@ + +R: Statistical Inference for Partially Observed Markov Processes + + + +

    Statistical Inference for Partially Observed Markov Processes + +

    +
    +
    +[Up] +[Top] +

    Documentation for package ‘pomp’ version 0.62-5

    + + + +

    Help Pages

    + + +

    + +A +B +C +D +E +F +G +I +L +M +N +O +P +R +S +T +V +W +misc +

    + + + + +
    pomp-packageInference for partially observed Markov processes
    + +

    -- A --

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    ABCEstimation by approximate Bayesian computation (ABC)
    abcEstimation by approximate Bayesian computation (ABC)
    abc-abcEstimation by approximate Bayesian computation (ABC)
    abc-classEstimation by approximate Bayesian computation (ABC)
    abc-methodEstimation by approximate Bayesian computation (ABC)
    abc-methodsEstimation by approximate Bayesian computation (ABC)
    abc-pompEstimation by approximate Bayesian computation (ABC)
    abc-probed.pompEstimation by approximate Bayesian computation (ABC)
    abcList-classEstimation by approximate Bayesian computation (ABC)
    accumulator variablesConstructor of the basic POMP object
    as-methodParticle filter
    as-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    as-methodProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    as.data.frame.pfilterd.pompParticle filter
    as.data.frame.pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    + +

    -- B --

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    basic.probesSome useful probes for partially-observed Markov processes
    Bayesian sequential Monte CarloThe Liu and West Bayesian particle filter
    bbsCompartmental epidemiological models
    blowfliesModel for Nicholson's blowflies.
    blowflies1Model for Nicholson's blowflies.
    blowflies2Model for Nicholson's blowflies.
    bsmcThe Liu and West Bayesian particle filter
    bsmc-methodThe Liu and West Bayesian particle filter
    bsmc-pompThe Liu and West Bayesian particle filter
    bsmc2The Liu and West Bayesian particle filter
    bsmc2-methodThe Liu and West Bayesian particle filter
    bsmc2-pompThe Liu and West Bayesian particle filter
    bspline.basisB-spline bases
    + +

    -- C --

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    c-abcEstimation by approximate Bayesian computation (ABC)
    c-abcListEstimation by approximate Bayesian computation (ABC)
    c-methodEstimation by approximate Bayesian computation (ABC)
    c-methodMaximum likelihood by iterated filtering
    c-methodThe particle Markov chain Metropolis-Hastings algorithm
    c-mifMaximum likelihood by iterated filtering
    c-mifListMaximum likelihood by iterated filtering
    c-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    c-pmcmcListThe particle Markov chain Metropolis-Hastings algorithm
    coef-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coef-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coef<-Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coef<--methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coef<--pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coerce-methodParticle filter
    coerce-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coerce-methodProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    compare.mifMaximum likelihood by iterated filtering
    cond.logLikParticle filter
    cond.logLik-methodParticle filter
    cond.logLik-pfilterd.pompParticle filter
    continueMaximum likelihood by iterated filtering
    continue-abcEstimation by approximate Bayesian computation (ABC)
    continue-methodEstimation by approximate Bayesian computation (ABC)
    continue-methodMaximum likelihood by iterated filtering
    continue-methodThe particle Markov chain Metropolis-Hastings algorithm
    continue-mifMaximum likelihood by iterated filtering
    continue-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    conv.recMaximum likelihood by iterated filtering
    conv.rec-abcEstimation by approximate Bayesian computation (ABC)
    conv.rec-abcListEstimation by approximate Bayesian computation (ABC)
    conv.rec-methodEstimation by approximate Bayesian computation (ABC)
    conv.rec-methodMaximum likelihood by iterated filtering
    conv.rec-methodThe particle Markov chain Metropolis-Hastings algorithm
    conv.rec-mifMaximum likelihood by iterated filtering
    conv.rec-mifListMaximum likelihood by iterated filtering
    conv.rec-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    conv.rec-pmcmcListThe particle Markov chain Metropolis-Hastings algorithm
    CsnippetC code snippets for accelerating computations
    Csnippet-classC code snippets for accelerating computations
    + +

    -- D --

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    daccaModel of cholera transmission for historic Bengal.
    data.arrayFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    data.array-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    data.array-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    data.frame-pompConstructor of the basic POMP object
    deulermultinomThe Euler-multinomial distributions and Gamma white-noise processes
    discrete.time.simPlug-ins for state-process models
    dmeasurepomp low-level interface
    dmeasure-methodpomp low-level interface
    dmeasure-pomppomp low-level interface
    dpriorpomp low-level interface
    dprior-methodpomp low-level interface
    dprior-pomppomp low-level interface
    dprocesspomp low-level interface
    dprocess-methodpomp low-level interface
    dprocess-pomppomp low-level interface
    + +

    -- E --

    + + + + + + + + + + + + + + + + +
    eff.sample.sizeParticle filter
    eff.sample.size-methodParticle filter
    eff.sample.size-pfilterd.pompParticle filter
    euler.simPlug-ins for state-process models
    euler.sirCompartmental epidemiological models
    eulermultinomThe Euler-multinomial distributions and Gamma white-noise processes
    Example pomp modelsExamples of the construction of POMP models
    + +

    -- F --

    + + + + + + + + +
    filter.meanParticle filter
    filter.mean-methodParticle filter
    filter.mean-pfilterd.pompParticle filter
    + +

    -- G --

    + + + + + + + + +
    gillespie.simPlug-ins for state-process models
    gillespie.sirCompartmental epidemiological models
    gompertzGompertz model with log-normal observations.
    + +

    -- I --

    + + + + + + + + +
    init.statepomp low-level interface
    init.state-methodpomp low-level interface
    init.state-pomppomp low-level interface
    + +

    -- L --

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    logLik-methodMaximum likelihood by iterated filtering
    logLik-methodParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    logLik-methodParticle filter
    logLik-methodThe particle Markov chain Metropolis-Hastings algorithm
    logLik-methodProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    logLik-methodParameter estimation by fitting the trajectory of a model's deterministic skeleton to data
    logLik-mifMaximum likelihood by iterated filtering
    logLik-nlfd.pompParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    logLik-pfilterd.pompParticle filter
    logLik-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    logLik-probed.pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    logLik-traj.matched.pompParameter estimation by fitting the trajectory of a model's deterministic skeleton to data
    logmeanexpThe log-mean-exp trick
    LondonYorkeHistorical childhood disease incidence data
    + +

    -- M --

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    matrix-pompConstructor of the basic POMP object
    MCMC proposal distributionsMCMC proposal distributions
    MCMC proposal functionsMCMC proposal distributions
    mifMaximum likelihood by iterated filtering
    mif-classMaximum likelihood by iterated filtering
    mif-methodMaximum likelihood by iterated filtering
    mif-methodsMaximum likelihood by iterated filtering
    mif-mifMaximum likelihood by iterated filtering
    mif-pfilterd.pompMaximum likelihood by iterated filtering
    mif-pompMaximum likelihood by iterated filtering
    mifList-classMaximum likelihood by iterated filtering
    mvn.diag.rwMCMC proposal distributions
    mvn.rwMCMC proposal distributions
    + +

    -- N --

    + + + + + + + + + + + + + + + + +
    nlfParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    nlf-methodParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    nlf-nlfd.pompParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    nlf-pompParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    nlfd.pomp-classParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    Nonlinear forecastingParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    numeric-pompConstructor of the basic POMP object
    + +

    -- O --

    + + + + + + + + + + + + + + +
    obsFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    obs-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    obs-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    onestep.densPlug-ins for state-process models
    onestep.simPlug-ins for state-process models
    ou2Two-dimensional discrete-time Ornstein-Uhlenbeck process
    + +

    -- P --

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1131 From noreply at r-forge.r-project.org Wed Mar 4 14:09:23 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Wed, 4 Mar 2015 14:09:23 +0100 (CET) Subject: [Pomp-commits] r1132 - pkg Message-ID: <20150304130923.7AE7218103A@r-forge.r-project.org> Author: kingaa Date: 2015-03-04 14:09:23 +0100 (Wed, 04 Mar 2015) New Revision: 1132 Modified: pkg/Makefile Log: - add html version of manual to package website Modified: pkg/Makefile =================================================================== --- pkg/Makefile 2015-03-04 13:09:19 UTC (rev 1131) +++ pkg/Makefile 2015-03-04 13:09:23 UTC (rev 1132) @@ -40,16 +40,16 @@ %.vignettes %.help %.data: export R_LIBS=$(CURDIR)/library %.bin %.check %.qcheck %.qqcheck %.xcheck %.crancheck %.upload %.publish %.clean %.install %.win: PKG = $*_$(shell perl -ne 'print $$1 if /Version:\s+(\d+\.\d+-\d+)/;' $*/DESCRIPTION) -pomp.vignettes: pomp.install pomp.manual +pomp.vignettes: pomp.install (cd ../www/vignettes; make) - cp pomp.pdf ../www/vignettes $(RCMD) Rdconv -t html pomp/inst/NEWS.Rd -o ../www/content/NEWS.html pompExamples.vignettes: pompExamples.install (cd pompExamples/vignettes; make) -pomp.help: pomp.install +pomp.help: pomp.install pomp.manual (cd ../www/help; make) + cp pomp.pdf ../www/help %.data: %.install cd $*/inst/data-R; make From noreply at r-forge.r-project.org Wed Mar 4 15:18:49 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Wed, 4 Mar 2015 15:18:49 +0100 (CET) Subject: [Pomp-commits] r1133 - www Message-ID: <20150304141849.5D8471876E1@r-forge.r-project.org> Author: kingaa Date: 2015-03-04 15:18:49 +0100 (Wed, 04 Mar 2015) New Revision: 1133 Modified: www/index.php Log: - different link for manual from homepage Modified: www/index.php =================================================================== --- www/index.php 2015-03-04 13:09:23 UTC (rev 1132) +++ www/index.php 2015-03-04 14:18:49 UTC (rev 1133) @@ -52,7 +52,7 @@
  • About pomp
  • Development Version (Rev. )
  • Release Version () on CRAN
    • -
  • pomp manual (HTML)
    • +
  • pomp manual (HTML)
  • pomp-announce mailing list archives
  • Package NEWS
  • Tutorial vignettes
    • From noreply at r-forge.r-project.org Wed Mar 4 16:10:11 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Wed, 4 Mar 2015 16:10:11 +0100 (CET) Subject: [Pomp-commits] r1134 - pkg www www/content www/help Message-ID: <20150304151011.B596C186D47@r-forge.r-project.org> Author: kingaa Date: 2015-03-04 16:10:11 +0100 (Wed, 04 Mar 2015) New Revision: 1134 Removed: www/help/00Index.html www/help/00frame_toc.html www/help/LondonYorke.html www/help/Makefile www/help/R.css www/help/abc.html www/help/basic-probes.html www/help/blowflies.html www/help/bsmc.html www/help/bsplines.html www/help/builder.html www/help/csnippet.html www/help/dacca.html www/help/design.html www/help/eulermultinom.html www/help/example.html www/help/gompertz.html www/help/index.html www/help/logmeanexp.html www/help/lowlevel.html www/help/mif.html www/help/nlf.html www/help/ou2.html www/help/parmat.html www/help/particles-mif.html www/help/pfilter.html www/help/plugins.html www/help/pmcmc.html www/help/pomp-fun.html www/help/pomp-methods.html www/help/pomp-package.html www/help/pomp.html www/help/pomp.pdf www/help/probe.html www/help/proposals.html www/help/ricker.html www/help/rw2.html www/help/sannbox.html www/help/simulate-pomp.html www/help/sir.html www/help/spect.html www/help/traj-match.html Modified: pkg/Makefile www/content/vignettes.htm www/index.php Log: Revert "- add html version of manual to package website" Modified: pkg/Makefile =================================================================== --- pkg/Makefile 2015-03-04 14:18:49 UTC (rev 1133) +++ pkg/Makefile 2015-03-04 15:10:11 UTC (rev 1134) @@ -32,25 +32,22 @@ %.dist %.manual %.vignettes: export R_QPDF=qpdf %.dist %.manual %.vignettes: export R_GSCMD=gs %.dist %.manual %.vignettes: export GS_QUALITY=ebook -%.dist %.manual %.vignettes %.help: export R_HOME=$(shell $(REXE) RHOME) +%.dist %.manual %.vignettes: export R_HOME=$(shell $(REXE) RHOME) %.check %.crancheck: export _R_CHECK_ALL_NON_ISO_C_=TRUE %.crancheck: export R_PROFILE_USER=./Rprofile %.check %.crancheck: export _R_CHECK_WALL_FORTRAN_=TRUE %.check %.xcheck: export POMP_FULL_TESTS=yes -%.vignettes %.help %.data: export R_LIBS=$(CURDIR)/library +%.vignettes %.data: export R_LIBS=$(CURDIR)/library %.bin %.check %.qcheck %.qqcheck %.xcheck %.crancheck %.upload %.publish %.clean %.install %.win: PKG = $*_$(shell perl -ne 'print $$1 if /Version:\s+(\d+\.\d+-\d+)/;' $*/DESCRIPTION) -pomp.vignettes: pomp.install +pomp.vignettes: pomp.install pomp.manual (cd ../www/vignettes; make) + cp pomp.pdf ../www/vignettes $(RCMD) Rdconv -t html pomp/inst/NEWS.Rd -o ../www/content/NEWS.html pompExamples.vignettes: pompExamples.install (cd pompExamples/vignettes; make) -pomp.help: pomp.install pomp.manual - (cd ../www/help; make) - cp pomp.pdf ../www/help - %.data: %.install cd $*/inst/data-R; make Modified: www/content/vignettes.htm =================================================================== --- www/content/vignettes.htm 2015-03-04 14:18:49 UTC (rev 1133) +++ www/content/vignettes.htm 2015-03-04 15:10:11 UTC (rev 1134) @@ -7,7 +7,6 @@ - - +
    parmatCreate a matrix of parameters
    particle filterParticle filter
    partransFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    partrans-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    partrans-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    periodic.bspline.basisB-spline bases
    pfilterParticle filter
    pfilter-methodParticle filter
    pfilter-pfilterd.pompParticle filter
    pfilter-pompParticle filter
    pfilterd.pomp-classParticle filter
    plot-abcEstimation by approximate Bayesian computation (ABC)
    plot-abcListEstimation by approximate Bayesian computation (ABC)
    plot-bsmcd.pompThe Liu and West Bayesian particle filter
    plot-methodEstimation by approximate Bayesian computation (ABC)
    plot-methodThe Liu and West Bayesian particle filter
    plot-methodMaximum likelihood by iterated filtering
    plot-methodThe particle Markov chain Metropolis-Hastings algorithm
    plot-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    plot-methodProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    plot-mifMaximum likelihood by iterated filtering
    plot-mifListMaximum likelihood by iterated filtering
    plot-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    plot-pmcmcListThe particle Markov chain Metropolis-Hastings algorithm
    plot-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    plot-probe.matched.pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    plot-probed.pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    plot-spect.pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    pluginsPlug-ins for state-process models
    pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-classThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-methodThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-methodsThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-pfilterd.pompThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-pompThe particle Markov chain Metropolis-Hastings algorithm
    pmcmcList-classThe particle Markov chain Metropolis-Hastings algorithm
    pompConstructor of the basic POMP object
    pomp constructorConstructor of the basic POMP object
    pomp low-level interfacepomp low-level interface
    pomp methodsFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    pomp packageInference for partially observed Markov processes
    POMP simulationSimulations of a partially-observed Markov process
    pomp-classConstructor of the basic POMP object
    pomp-methodConstructor of the basic POMP object
    pomp-methodsFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    pomp-pompConstructor of the basic POMP object
    pompExampleExamples of the construction of POMP models
    pompLoadpomp low-level interface
    pompLoad-methodpomp low-level interface
    pompLoad-pomppomp low-level interface
    pompUnloadpomp low-level interface
    pompUnload-methodpomp low-level interface
    pompUnload-pomppomp low-level interface
    Power spectrum computation and matchingPower spectrum computation and spectrum-matching for partially-observed Markov processes
    power spectrum computation and matchingPower spectrum computation and spectrum-matching for partially-observed Markov processes
    pred.meanParticle filter
    pred.mean-methodParticle filter
    pred.mean-pfilterd.pompParticle filter
    pred.varParticle filter
    pred.var-methodParticle filter
    pred.var-pfilterd.pompParticle filter
    print-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    print-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    probeProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    Probe functionsSome useful probes for partially-observed Markov processes
    probe functionsSome useful probes for partially-observed Markov processes
    probe-methodProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    probe-pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    probe-probed.pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    probe.acf (R code)
    pomp package manual(HTML)(PDF)(PDF)
    Deleted: www/help/00Index.html =================================================================== --- www/help/00Index.html 2015-03-04 14:18:49 UTC (rev 1133) +++ www/help/00Index.html 2015-03-04 15:10:11 UTC (rev 1134) @@ -1,810 +0,0 @@ - -R: Statistical Inference for Partially Observed Markov Processes - - - -

    Statistical Inference for Partially Observed Markov Processes - -

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    -[Up] -[Top] -

    Documentation for package ‘pomp’ version 0.62-5

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    Help Pages

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    - -A -B -C -D -E -F -G -I -L -M -N -O -P -R -S -T -V -W -misc -

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    pomp-packageInference for partially observed Markov processes
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    -- A --

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    ABCEstimation by approximate Bayesian computation (ABC)
    abcEstimation by approximate Bayesian computation (ABC)
    abc-abcEstimation by approximate Bayesian computation (ABC)
    abc-classEstimation by approximate Bayesian computation (ABC)
    abc-methodEstimation by approximate Bayesian computation (ABC)
    abc-methodsEstimation by approximate Bayesian computation (ABC)
    abc-pompEstimation by approximate Bayesian computation (ABC)
    abc-probed.pompEstimation by approximate Bayesian computation (ABC)
    abcList-classEstimation by approximate Bayesian computation (ABC)
    accumulator variablesConstructor of the basic POMP object
    as-methodParticle filter
    as-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    as-methodProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    as.data.frame.pfilterd.pompParticle filter
    as.data.frame.pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
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    -- B --

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    basic.probesSome useful probes for partially-observed Markov processes
    Bayesian sequential Monte CarloThe Liu and West Bayesian particle filter
    bbsCompartmental epidemiological models
    blowfliesModel for Nicholson's blowflies.
    blowflies1Model for Nicholson's blowflies.
    blowflies2Model for Nicholson's blowflies.
    bsmcThe Liu and West Bayesian particle filter
    bsmc-methodThe Liu and West Bayesian particle filter
    bsmc-pompThe Liu and West Bayesian particle filter
    bsmc2The Liu and West Bayesian particle filter
    bsmc2-methodThe Liu and West Bayesian particle filter
    bsmc2-pompThe Liu and West Bayesian particle filter
    bspline.basisB-spline bases
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    -- C --

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    c-abcEstimation by approximate Bayesian computation (ABC)
    c-abcListEstimation by approximate Bayesian computation (ABC)
    c-methodEstimation by approximate Bayesian computation (ABC)
    c-methodMaximum likelihood by iterated filtering
    c-methodThe particle Markov chain Metropolis-Hastings algorithm
    c-mifMaximum likelihood by iterated filtering
    c-mifListMaximum likelihood by iterated filtering
    c-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    c-pmcmcListThe particle Markov chain Metropolis-Hastings algorithm
    coef-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coef-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coef<-Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coef<--methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coef<--pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coerce-methodParticle filter
    coerce-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    coerce-methodProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    compare.mifMaximum likelihood by iterated filtering
    cond.logLikParticle filter
    cond.logLik-methodParticle filter
    cond.logLik-pfilterd.pompParticle filter
    continueMaximum likelihood by iterated filtering
    continue-abcEstimation by approximate Bayesian computation (ABC)
    continue-methodEstimation by approximate Bayesian computation (ABC)
    continue-methodMaximum likelihood by iterated filtering
    continue-methodThe particle Markov chain Metropolis-Hastings algorithm
    continue-mifMaximum likelihood by iterated filtering
    continue-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    conv.recMaximum likelihood by iterated filtering
    conv.rec-abcEstimation by approximate Bayesian computation (ABC)
    conv.rec-abcListEstimation by approximate Bayesian computation (ABC)
    conv.rec-methodEstimation by approximate Bayesian computation (ABC)
    conv.rec-methodMaximum likelihood by iterated filtering
    conv.rec-methodThe particle Markov chain Metropolis-Hastings algorithm
    conv.rec-mifMaximum likelihood by iterated filtering
    conv.rec-mifListMaximum likelihood by iterated filtering
    conv.rec-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    conv.rec-pmcmcListThe particle Markov chain Metropolis-Hastings algorithm
    CsnippetC code snippets for accelerating computations
    Csnippet-classC code snippets for accelerating computations
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    -- D --

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    daccaModel of cholera transmission for historic Bengal.
    data.arrayFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    data.array-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    data.array-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    data.frame-pompConstructor of the basic POMP object
    deulermultinomThe Euler-multinomial distributions and Gamma white-noise processes
    discrete.time.simPlug-ins for state-process models
    dmeasurepomp low-level interface
    dmeasure-methodpomp low-level interface
    dmeasure-pomppomp low-level interface
    dpriorpomp low-level interface
    dprior-methodpomp low-level interface
    dprior-pomppomp low-level interface
    dprocesspomp low-level interface
    dprocess-methodpomp low-level interface
    dprocess-pomppomp low-level interface
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    -- E --

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    eff.sample.sizeParticle filter
    eff.sample.size-methodParticle filter
    eff.sample.size-pfilterd.pompParticle filter
    euler.simPlug-ins for state-process models
    euler.sirCompartmental epidemiological models
    eulermultinomThe Euler-multinomial distributions and Gamma white-noise processes
    Example pomp modelsExamples of the construction of POMP models
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    -- F --

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    filter.meanParticle filter
    filter.mean-methodParticle filter
    filter.mean-pfilterd.pompParticle filter
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    -- G --

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    gillespie.simPlug-ins for state-process models
    gillespie.sirCompartmental epidemiological models
    gompertzGompertz model with log-normal observations.
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    -- I --

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    init.statepomp low-level interface
    init.state-methodpomp low-level interface
    init.state-pomppomp low-level interface
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    -- L --

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    logLik-methodMaximum likelihood by iterated filtering
    logLik-methodParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    logLik-methodParticle filter
    logLik-methodThe particle Markov chain Metropolis-Hastings algorithm
    logLik-methodProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    logLik-methodParameter estimation by fitting the trajectory of a model's deterministic skeleton to data
    logLik-mifMaximum likelihood by iterated filtering
    logLik-nlfd.pompParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    logLik-pfilterd.pompParticle filter
    logLik-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    logLik-probed.pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    logLik-traj.matched.pompParameter estimation by fitting the trajectory of a model's deterministic skeleton to data
    logmeanexpThe log-mean-exp trick
    LondonYorkeHistorical childhood disease incidence data
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    -- M --

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    matrix-pompConstructor of the basic POMP object
    MCMC proposal distributionsMCMC proposal distributions
    MCMC proposal functionsMCMC proposal distributions
    mifMaximum likelihood by iterated filtering
    mif-classMaximum likelihood by iterated filtering
    mif-methodMaximum likelihood by iterated filtering
    mif-methodsMaximum likelihood by iterated filtering
    mif-mifMaximum likelihood by iterated filtering
    mif-pfilterd.pompMaximum likelihood by iterated filtering
    mif-pompMaximum likelihood by iterated filtering
    mifList-classMaximum likelihood by iterated filtering
    mvn.diag.rwMCMC proposal distributions
    mvn.rwMCMC proposal distributions
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    -- N --

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    nlfParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    nlf-methodParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    nlf-nlfd.pompParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    nlf-pompParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    nlfd.pomp-classParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    Nonlinear forecastingParameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)
    numeric-pompConstructor of the basic POMP object
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    -- O --

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    obsFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    obs-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    obs-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    onestep.densPlug-ins for state-process models
    onestep.simPlug-ins for state-process models
    ou2Two-dimensional discrete-time Ornstein-Uhlenbeck process
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    -- P --

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1134 From noreply at r-forge.r-project.org Thu Mar 5 00:04:11 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Thu, 5 Mar 2015 00:04:11 +0100 (CET) Subject: [Pomp-commits] r1135 - www/vignettes Message-ID: <20150304230412.02198187A4B@r-forge.r-project.org> Author: kingaa Date: 2015-03-05 00:04:11 +0100 (Thu, 05 Mar 2015) New Revision: 1135 Added: www/vignettes/pomp.pdf Log: - put manual back in Added: www/vignettes/pomp.pdf =================================================================== --- www/vignettes/pomp.pdf (rev 0) +++ www/vignettes/pomp.pdf 2015-03-04 23:04:11 UTC (rev 1135) @@ -0,0 +1,2646 @@ +%PDF-1.5 +%???? +1 0 obj +<< /Type /ObjStm /Length 4540 /Filter /FlateDecode /N 99 /First 841 >> +stream +x??\is?8??????vRS!????????I????l??Rl???,y$9??_?OM?"i[v??[[? +?G?????UT?.\(L??+l?)\!Ut?/????4???.?BV? d?? +'U???[ ???????,?-??8? ++?????Ph?L!c???C?Z"Rh??*?t^FE?Ma?[X?|AL? ? g??PxI???+????0?e?c??*?2\?T?`? ?mU???Y??? +-?[Izs?????d+???l??Yy:?q?,???`?Z?e??Z??I???? vp ??"E:??AS: +~???C?? ???B? ?C??,Y@???8? +W?ta?? 5C???5???I??l??@???C?h$?????(???2?"??!"Q??;F??"? c?`??8(*X????e00mY?;?????b?^??G?Y?j??.????^??R????;o??T??????p7?]?(?GQ??7?T??y????u??2?????????y?|???????????/K?????6?o\?x<_72?#G6o??a? ???x??7???lo?R???? ???F?l_?d^??gg?w?GG???;=?am6?d?????= ???= ?)??#hPB???l+!?[(a=??4m?_??? +?? ?_v?????)??\?)w?V2\?S?O?#>c????n?'?+?v?]?v?a?]???6;b???r_%????????????????q?4???f?????U??-0?q8?????? +?_i*~Gbn?J?*S??????j??????&8??(??????{G???S??.???^????????F{>???>Z???I?????Hf?R?R#?B +\z??**?i?/)K????????+?H?=}?~?EE???ci?-'U7??=J???h???D!????????bv?r_??Y?)?????I)?{p:?*3?@.%?HM9L?^?E*?3?!v??????i?UR??*;4??W6?S)?????k??*??rj?c????~u??*??t?? 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JSf?[?0S???A#??2l?Dx????????s?}??I?????U C?6t]}&?%??????J:`>T??S???X+?$??U???p??i5IV?^D?I?Fdi?_Y?f ??K.?wz? 5???????G ?Q??;???FYxF4?, OK??.?*+a!?z{r ?2Ii*?`?(?[?\???pc$???SGN??e/??(??/??????y?m? bS?Db???P?????R? +??z?qI"5mM??Y!?Q7?? lNa9??t??;Ft???I?????g?? J?mZ?:{??QY??????u??E??#x 6??) ???????????Uy(?~{l?}Z7Uz??????? ?p{?.R????/??*?h?@ +?b?3??,\GTu?P????8???K?s +???f?\ ???????????:???x?9+P???#m???m??|H +?? ?v??9?=??5?? ?6?????xdD??Es??-70O?????_L???,!?????)???Nr,h$??z?????????????QDjv?I????)?c^@z???????B?a + ?J??? 9%?h?)x>??xL>??8`? ??? +,d ????sS?A@?^r?? ????+?Q~n? +}??7??$??I??:{No??c L?)f ?N??????//8Qp>+? +`Bj?(C????b?m?c??~M????S?,.????/??&I|#0 ??W???? +?T??{Y???*cs???3?????D?????{??p?? +kj??$e?^???V???/???I ?f?b???-?|\?_??*????,?????G?%E?m???5?????5HY? +QyU'??A#??K????U?~????^I??$???~?? +?? +O??O??>y???&u\??*ooL|?C??R??!? +??&????\S??lw??&??l????????w??m$??J??&!???{?q,???Y??? ?r??s [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1135 From noreply at r-forge.r-project.org Thu Mar 5 14:21:07 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Thu, 5 Mar 2015 14:21:07 +0100 (CET) Subject: [Pomp-commits] r1136 - in pkg/pomp: . R Message-ID: <20150305132107.D7B93187872@r-forge.r-project.org> Author: kingaa Date: 2015-03-05 14:21:07 +0100 (Thu, 05 Mar 2015) New Revision: 1136 Modified: pkg/pomp/DESCRIPTION pkg/pomp/R/builder.R pkg/pomp/R/pomp.R Log: - add secret .filedir and .filename arguments to 'pomp.internal' to allow saving of C codes in arbitrary directory Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-04 23:04:11 UTC (rev 1135) +++ pkg/pomp/DESCRIPTION 2015-03-05 13:21:07 UTC (rev 1136) @@ -1,8 +1,8 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.62-5 -Date: 2015-03-02 +Version: 0.62-6 +Date: 2015-03-05 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), person(given=c("Edward","L."),family="Ionides",role=c("aut")), Modified: pkg/pomp/R/builder.R =================================================================== --- pkg/pomp/R/builder.R 2015-03-04 23:04:11 UTC (rev 1135) +++ pkg/pomp/R/builder.R 2015-03-05 13:21:07 UTC (rev 1136) @@ -1,8 +1,8 @@ -pompCBuilder <- function (name = NULL, +pompCBuilder <- function (name = NULL, dir = NULL, statenames, paramnames, covarnames, obsnames, rmeasure, dmeasure, step.fn, skeleton, parameter.transform, parameter.inv.transform, - rprior, dprior, globals, dir = NULL, + rprior, dprior, globals, verbose = getOption("verbose",FALSE)) { Modified: pkg/pomp/R/pomp.R =================================================================== --- pkg/pomp/R/pomp.R 2015-03-04 23:04:11 UTC (rev 1135) +++ pkg/pomp/R/pomp.R 2015-03-05 13:21:07 UTC (rev 1136) @@ -9,7 +9,8 @@ obsnames, statenames, paramnames, covarnames, zeronames, PACKAGE, parameter.transform, parameter.inv.transform, - globals, userdata, ..., .solibfile, + globals, userdata, ..., + .solibfile, .filename, .filedir, verbose = getOption("verbose",FALSE)) { ## preliminary error checking @@ -18,6 +19,8 @@ if (missing(t0)) stop(sQuote("t0")," is a required argument") if (missing(params)) params <- numeric(0) if (missing(.solibfile)) .solibfile <- list() + if (missing(.filename)) .filename <- NULL + if (missing(.filedir)) .filedir <- NULL if (missing(userdata)) userdata <- list() added.userdata <- list(...) @@ -144,6 +147,8 @@ paramnames=paramnames, covarnames=covarnames, globals=globals, + name=.filename, + dir=.filedir, verbose=verbose ), snips From noreply at r-forge.r-project.org Thu Mar 5 15:44:42 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Thu, 5 Mar 2015 15:44:42 +0100 (CET) Subject: [Pomp-commits] r1137 - in pkg/pomp: . R Message-ID: <20150305144442.9EF141858DF@r-forge.r-project.org> Author: kingaa Date: 2015-03-05 15:44:42 +0100 (Thu, 05 Mar 2015) New Revision: 1137 Modified: pkg/pomp/DESCRIPTION pkg/pomp/R/mif.R Log: - in 'mif', var.factor=1 is the default. Remove stray error blocking this. Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-05 13:21:07 UTC (rev 1136) +++ pkg/pomp/DESCRIPTION 2015-03-05 14:44:42 UTC (rev 1137) @@ -1,7 +1,7 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.62-6 +Version: 0.62-7 Date: 2015-03-05 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), Modified: pkg/pomp/R/mif.R =================================================================== --- pkg/pomp/R/mif.R 2015-03-05 13:21:07 UTC (rev 1136) +++ pkg/pomp/R/mif.R 2015-03-05 14:44:42 UTC (rev 1137) @@ -408,8 +408,6 @@ if (missing(Np)) stop("mif error: ",sQuote("Np")," must be specified",call.=FALSE) - if (missing(var.factor)) - stop("mif error: ",sQuote("var.factor")," must be specified",call.=FALSE) cooling.type <- match.arg(cooling.type) From noreply at r-forge.r-project.org Fri Mar 6 13:44:34 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Fri, 6 Mar 2015 13:44:34 +0100 (CET) Subject: [Pomp-commits] r1138 - in pkg/pomp: . R tests Message-ID: <20150306124434.DF7C91845E3@r-forge.r-project.org> Author: kingaa Date: 2015-03-06 13:44:34 +0100 (Fri, 06 Mar 2015) New Revision: 1138 Modified: pkg/pomp/DESCRIPTION pkg/pomp/R/abc.R pkg/pomp/R/mif.R pkg/pomp/R/pmcmc.R pkg/pomp/tests/gompertz.Rout.save Log: - add names to dimnames of conv.rec in abc, pmcmc, and mif objects Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-05 14:44:42 UTC (rev 1137) +++ pkg/pomp/DESCRIPTION 2015-03-06 12:44:34 UTC (rev 1138) @@ -1,8 +1,8 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.62-7 -Date: 2015-03-05 +Version: 0.62-8 +Date: 2015-03-06 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), person(given=c("Edward","L."),family="Ionides",role=c("aut")), Modified: pkg/pomp/R/abc.R =================================================================== --- pkg/pomp/R/abc.R 2015-03-05 14:44:42 UTC (rev 1137) +++ pkg/pomp/R/abc.R 2015-03-06 12:44:34 UTC (rev 1138) @@ -85,8 +85,8 @@ nrow=Nabc+1, ncol=length(theta), dimnames=list( - rownames=seq(from=0,to=Nabc,by=1), - colnames=names(theta) + iteration=seq(from=0,to=Nabc,by=1), + variable=names(theta) ) ) @@ -283,6 +283,7 @@ object at conv.rec[,colnames(obj at conv.rec)], obj at conv.rec[-1,] ) + names(dimnames(obj at conv.rec)) <- c("iteration","variable") obj at Nabc <- as.integer(ndone+Nabc) obj Modified: pkg/pomp/R/mif.R =================================================================== --- pkg/pomp/R/mif.R 2015-03-05 14:44:42 UTC (rev 1137) +++ pkg/pomp/R/mif.R 2015-03-06 12:44:34 UTC (rev 1138) @@ -244,8 +244,8 @@ nrow=Nmif+1, ncol=length(theta)+2, dimnames=list( - seq(.ndone,.ndone+Nmif), - c('loglik','nfail',names(theta)) + iteration=seq(.ndone,.ndone+Nmif), + variable=c('loglik','nfail',names(theta)) ) ) conv.rec[1L,] <- c(NA,NA,theta) @@ -538,6 +538,7 @@ object at conv.rec, obj at conv.rec[-1L,colnames(object at conv.rec)] ) + names(dimnames(obj at conv.rec)) <- c("iteration","variable") obj at Nmif <- as.integer(ndone+Nmif) obj Modified: pkg/pomp/R/pmcmc.R =================================================================== --- pkg/pomp/R/pmcmc.R 2015-03-05 14:44:42 UTC (rev 1137) +++ pkg/pomp/R/pmcmc.R 2015-03-06 12:44:34 UTC (rev 1138) @@ -90,8 +90,8 @@ nrow=Nmcmc+1, ncol=length(theta)+3, dimnames=list( - rownames=seq(from=0,to=Nmcmc,by=1), - colnames=c('loglik','log.prior','nfail',names(theta)) + iteration=seq(from=0,to=Nmcmc,by=1), + variable=c('loglik','log.prior','nfail',names(theta)) ) ) @@ -300,6 +300,7 @@ object at conv.rec[,colnames(obj at conv.rec)], obj at conv.rec[-1,] ) + names(dimnames(obj at conv.rec)) <- c("iteration","variable") obj at Nmcmc <- as.integer(ndone+Nmcmc) obj } Modified: pkg/pomp/tests/gompertz.Rout.save =================================================================== --- pkg/pomp/tests/gompertz.Rout.save 2015-03-05 14:44:42 UTC (rev 1137) +++ pkg/pomp/tests/gompertz.Rout.save 2015-03-06 12:44:34 UTC (rev 1138) @@ -77,13 +77,14 @@ K r sigma tau X.0 1.0478 0.1992 0.1000 0.1000 1.0000 > conv.rec(mf) - loglik nfail K r sigma tau X.0 -0 30.35 0 0.00000 -1.609 -2.303 -2.303 0 -1 30.59 0 0.01048 -1.609 -2.303 -2.303 0 -2 30.96 0 0.02378 -1.610 -2.303 -2.303 0 -3 29.78 0 0.03161 -1.607 -2.303 -2.303 0 -4 31.18 0 0.03785 -1.611 -2.303 -2.303 0 -5 NA NA 0.04671 -1.613 -2.303 -2.303 0 + variable +iteration loglik nfail K r sigma tau X.0 + 0 30.35 0 0.00000 -1.609 -2.303 -2.303 0 + 1 30.59 0 0.01048 -1.609 -2.303 -2.303 0 + 2 30.96 0 0.02378 -1.610 -2.303 -2.303 0 + 3 29.78 0 0.03161 -1.607 -2.303 -2.303 0 + 4 31.18 0 0.03785 -1.611 -2.303 -2.303 0 + 5 NA NA 0.04671 -1.613 -2.303 -2.303 0 > conv.rec(mf,transform=TRUE) K r sigma tau X.0 loglik nfail 0 1.000 0.2000 0.1 0.1 1 30.35 0 @@ -93,21 +94,23 @@ 4 1.039 0.1996 0.1 0.1 1 31.18 0 5 1.048 0.1992 0.1 0.1 1 NA NA > conv.rec(mf,c("loglik","r")) - loglik r -0 30.35 -1.609 -1 30.59 -1.609 -2 30.96 -1.610 -3 29.78 -1.607 -4 31.18 -1.611 -5 NA -1.613 + variable +iteration loglik r + 0 30.35 -1.609 + 1 30.59 -1.609 + 2 30.96 -1.610 + 3 29.78 -1.607 + 4 31.18 -1.611 + 5 NA -1.613 > try(conv.rec(mf,c("loglik","r"),transform=FALSE)) - loglik r -0 30.35 -1.609 -1 30.59 -1.609 -2 30.96 -1.610 -3 29.78 -1.607 -4 31.18 -1.611 -5 NA -1.613 + variable +iteration loglik r + 0 30.35 -1.609 + 1 30.59 -1.609 + 2 30.96 -1.610 + 3 29.78 -1.607 + 4 31.18 -1.611 + 5 NA -1.613 > try(conv.rec(mf,c("loglik","r"),transform=TRUE)) loglik r 0 30.35 0.2000 @@ -133,4 +136,4 @@ > > proc.time() user system elapsed - 1.576 0.052 1.652 + 1.838 0.040 1.853 From noreply at r-forge.r-project.org Thu Mar 12 12:34:30 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Thu, 12 Mar 2015 12:34:30 +0100 (CET) Subject: [Pomp-commits] r1139 - in www: content vignettes Message-ID: <20150312113430.1650A1876D9@r-forge.r-project.org> Author: kingaa Date: 2015-03-12 12:34:29 +0100 (Thu, 12 Mar 2015) New Revision: 1139 Added: www/vignettes/abc.rda www/vignettes/algorithm2e.sty www/vignettes/cleveref.sty www/vignettes/gompertz-mif.rda www/vignettes/jss.bst www/vignettes/jss.cls www/vignettes/nlf-mif-compare.rda www/vignettes/pmcmc.rda www/vignettes/pompjss.R www/vignettes/pompjss.Rnw www/vignettes/pompjss.bib www/vignettes/pompjss.pdf www/vignettes/ricker-comparison.rda www/vignettes/ricker-mif.rda www/vignettes/ricker-probe-match.rda www/vignettes/timing.rda Modified: www/content/vignettes.htm www/vignettes/getting_started.R www/vignettes/getting_started.Rmd www/vignettes/getting_started.html www/vignettes/pomp.pdf Log: - add pompjss paper to vignettes Modified: www/content/vignettes.htm =================================================================== --- www/content/vignettes.htm 2015-03-06 12:44:34 UTC (rev 1138) +++ www/content/vignettes.htm 2015-03-12 11:34:29 UTC (rev 1139) @@ -2,6 +2,11 @@
    parmatCreate a matrix of parameters
    particle filterParticle filter
    partransFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    partrans-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    partrans-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    periodic.bspline.basisB-spline bases
    pfilterParticle filter
    pfilter-methodParticle filter
    pfilter-pfilterd.pompParticle filter
    pfilter-pompParticle filter
    pfilterd.pomp-classParticle filter
    plot-abcEstimation by approximate Bayesian computation (ABC)
    plot-abcListEstimation by approximate Bayesian computation (ABC)
    plot-bsmcd.pompThe Liu and West Bayesian particle filter
    plot-methodEstimation by approximate Bayesian computation (ABC)
    plot-methodThe Liu and West Bayesian particle filter
    plot-methodMaximum likelihood by iterated filtering
    plot-methodThe particle Markov chain Metropolis-Hastings algorithm
    plot-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    plot-methodProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    plot-mifMaximum likelihood by iterated filtering
    plot-mifListMaximum likelihood by iterated filtering
    plot-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    plot-pmcmcListThe particle Markov chain Metropolis-Hastings algorithm
    plot-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    plot-probe.matched.pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    plot-probed.pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    plot-spect.pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    pluginsPlug-ins for state-process models
    pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-classThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-methodThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-methodsThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-pfilterd.pompThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-pmcmcThe particle Markov chain Metropolis-Hastings algorithm
    pmcmc-pompThe particle Markov chain Metropolis-Hastings algorithm
    pmcmcList-classThe particle Markov chain Metropolis-Hastings algorithm
    pompConstructor of the basic POMP object
    pomp constructorConstructor of the basic POMP object
    pomp low-level interfacepomp low-level interface
    pomp methodsFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    pomp packageInference for partially observed Markov processes
    POMP simulationSimulations of a partially-observed Markov process
    pomp-classConstructor of the basic POMP object
    pomp-methodConstructor of the basic POMP object
    pomp-methodsFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    pomp-pompConstructor of the basic POMP object
    pompExampleExamples of the construction of POMP models
    pompLoadpomp low-level interface
    pompLoad-methodpomp low-level interface
    pompLoad-pomppomp low-level interface
    pompUnloadpomp low-level interface
    pompUnload-methodpomp low-level interface
    pompUnload-pomppomp low-level interface
    Power spectrum computation and matchingPower spectrum computation and spectrum-matching for partially-observed Markov processes
    power spectrum computation and matchingPower spectrum computation and spectrum-matching for partially-observed Markov processes
    pred.meanParticle filter
    pred.mean-methodParticle filter
    pred.mean-pfilterd.pompParticle filter
    pred.varParticle filter
    pred.var-methodParticle filter
    pred.var-pfilterd.pompParticle filter
    print-methodFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    print-pompFunctions for manipulating, displaying, and extracting information from objects of the 'pomp' class
    probeProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    Probe functionsSome useful probes for partially-observed Markov processes
    probe functionsSome useful probes for partially-observed Markov processes
    probe-methodProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    probe-pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    probe-probed.pompProbe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.
    probe.acfSome useful probes for partially-observed Markov processes
    probe.ccfSome useful probes for partially-observed Markov processes
    probe.marginalSome useful probes for partially-observed Markov processes
    + + + + + Added: www/vignettes/abc.rda =================================================================== --- www/vignettes/abc.rda (rev 0) +++ www/vignettes/abc.rda 2015-03-12 11:34:29 UTC (rev 1139) @@ -0,0 +1,4823 @@ +???y4?????6)?$)????$%EJHEQYJIJ!??????/cc7?}??5I?V??????>?{~?>????j??????????u8?i?(?6Y?????????????/?v6.?U,]}??R???????ll???gV?????P?S???o?A[??7v2(?%#???HW?e.??E???????(-K?$3\ +?????????V??0Bc??3??P)$???>?['K??4?#??????w?I? ??4a??9r?G???XO?X?~J????4E^?F?1?Z?x?x?e~?P??U( ?~?Zl-C?????? ???\i???????w?#?3@????s??#???kOV??SmY???!?'?=(?o???b??%???:?|?i?????Bc??????@???`???WP.j?&???????q?n*????Q?Z????&\?~?U^?????8H%???E????mt ??0?????%E?|???2???n6?qi?2t??}?ME?k?=wC??7?V??;:;???t???,9tZ?:?j3?z??Zl???'zr,???Dt????-??"S?????c?????/:???`?6?\??C{????,???5(??2??S??fE????????e??=??????????GQ?u???]? ?[h?r??=;CM ????????HKf?_ ?}? ????.???,{?>E??hy??BiI?1hsr???2s????'Z?^??v +M?o Ds???'???????C~?`q??????Z0os?w*U?5.!wVm??? ?? ???=D W???1m3||7??+????PW?????+j???l? + at c?????@??,^KS?!etv? +j??)??C???mu?E at 2k?mL?@??Q?/'??J???1?62?%t?#k?????$?????F#?"n???=3???6?C?:?B?6k??&v?Y Eu1??G?^%?k?m????????0n?W;? ?????D?????C? +?2?x3??????8?(?????H?.F\j?A??r?? 9?i?????????[U?IT???+Q?w????m???)V????{ ??D?U'???7??I?D?/??LA??????? ??x]d??g^?B??? +;s???E??~y3??[???fQ??????D???????Iy?<=ra??? ?%P?&??#??V??????'r?????Xte??|??????'? +(??H ?????????x??.R??^5?t???????"??>????hI^??-?n??!~@ +E?S??????A??}??????k_?r$?V!C?d??@?B-????:'j???;?????LUW8tU?F??I4_k???B?? ?[LW4?y/R??`????%?j??}?h=[.?:??C"?+?9A????X??S?? +{????c??J.G?????h??-v?????-k??.?]??s??s???J??wh???YL?g???+'?8???{a?>?c? +MF??~??Z?5=~ ????S?Q????????:}?k????^??_???\9??B???xb??.{F????m=??n??Y+y??cV;??????w? ]0S?? +;???m}?&[? ?+?D?c?}?3?@?v?H?6???~?p??gP?Ro? +X?hUXk?n +?'?_?????6:{9A??{?b?%??xw$??@???yS?TJ?V?? ???v???(?wx??g????????????{?w??uN?:???1??X?"[??m? ;??},??!?FT?y?????6??Z??<3?????D?????u`???2?&?f? [?O?)???1?@?>?j???83ia?-%E?? +@??1?zL?????+n????"2?-?"??3r??"%?zJ?t??*???U=?w9??0?_'???-???? ???ZF??(>???'J??B??q7E?d|^??????2%S?-??E?*;?%?F??'?O??8? ??_-*?*?????H2?:?"????/?]L5??{?

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+??&?nEQ??*???????By?? ?[(?m?{'?????????Q??,?}g ?????????;G+~???n?4???O?????"#-F????P?????<I?? +G???[?L +??|6???ejo?????`??P???A/v?5????8??*????@W.?bx?]3?????ho/vj???????- p??x??O-;t9pE ?{????$tOu[??G??????6??qc?(??|??CS???X?)?>]???b???1??E??? ?G?????[hv[Qu?? +?%????F??E??n9?Mm??:???????1\????h?? b??????q>??{?.j?G????G?3Pk?~???u(_I?IecC?? +?Dg?)???=,P???;:??N?????D???9K?^??9?t????T???Q?Zz?l?#T?6{?w ?{TE}?Ql~hg??1??+8S?? ?'r?e?e?n?????U??=??????C=`j +???8??{viEc???.?????v??????s(y ? ?NIB?uP??? ++|%? +?~?e????hi????????#??*A?r? ?lh????~??????C?'?_%f???????I4z?X4?C9???N????[?@???U???????xr at P~??u????TPP?p@? +??d[5W?xY?????RN?H sx??Ug??????4?f???????H?~???W?5??l?EP??&?cAC???gWw?????sF\ :?_?JvQ??=i?5T(%H&g??Z??K?f5??7?9????-@ AMK????I?rL??????V?$<qU?m?+?Mn?????'????DQA?L??nT:1????G)=?????????O???.?c > +a??(?f&n?/??;????DT???Y?7 +????rn?\?,?X$?)???O~-{?????g?q???(QU????{n? +D???vU +@?>??=bJ???G??^???s6??.?&????Y????ml?F?????i???|9??u???????p??p???(Z??z??$??dD???A????UZgQ??{?4?b +?t_??P??????-??u??m???N??}?????`??P???T???,?DQ$C??)4H??@D??I"? +i??Y* [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1139 From noreply at r-forge.r-project.org Fri Mar 13 19:42:28 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Fri, 13 Mar 2015 19:42:28 +0100 (CET) Subject: [Pomp-commits] r1140 - www/vignettes Message-ID: <20150313184228.7BE9C1874E9@r-forge.r-project.org> Author: kingaa Date: 2015-03-13 19:42:28 +0100 (Fri, 13 Mar 2015) New Revision: 1140 Modified: www/vignettes/pompjss.Rnw Log: - fixed a typo Modified: www/vignettes/pompjss.Rnw =================================================================== --- www/vignettes/pompjss.Rnw 2015-03-12 11:34:29 UTC (rev 1139) +++ www/vignettes/pompjss.Rnw 2015-03-13 18:42:28 UTC (rev 1140) @@ -281,7 +281,7 @@ The POMP structure implies that this joint density is determined by the initial density, $f_{X_{0}}(x_{0};\theta)$, together with the conditional transition probability density, $f_{X_{n}|X_{n-1}}(x_{n}\given x_{n-1}\giventh\theta)$, and the measurement density, $f_{Y_{n}|X_{n}}(y_{n}\given x_{n}\giventh\theta)$, for $1\leq n\leq N$. In particular, we have \begin{equation}\label{eq:joint-dens} - f_{X_{0:N},Y_{1:N}}(x_{0:n},y_{1:n};\theta) = f_{X_0}(x_0;\theta)\,\prod_{n=1}^N\!f_{X_n | X_{n-1}}(x_n|x_{n-1};\theta)\,f_{Y_n|X_n}(y_n|x_n;\theta). + f_{X_{0:N},Y_{1:N}}(x_{0:N},y_{1:N};\theta) = f_{X_0}(x_0;\theta)\,\prod_{n=1}^N\!f_{X_n | X_{n-1}}(x_n|x_{n-1};\theta)\,f_{Y_n|X_n}(y_n|x_n;\theta). \end{equation} Note that this formalism allows the transition density, $f_{X_{n}|X_{n-1}}$, and measurement density, $f_{Y_{n}|X_{n}}$, to depend explicitly on $n$. From noreply at r-forge.r-project.org Fri Mar 13 19:43:51 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Fri, 13 Mar 2015 19:43:51 +0100 (CET) Subject: [Pomp-commits] r1141 - pkg/pomp pkg/pomp/R pkg/pomp/inst/include pkg/pomp/src www/vignettes Message-ID: <20150313184351.ABAB11874E9@r-forge.r-project.org> Author: kingaa Date: 2015-03-13 19:43:50 +0100 (Fri, 13 Mar 2015) New Revision: 1141 Modified: pkg/pomp/DESCRIPTION pkg/pomp/R/pomp.R pkg/pomp/inst/include/pomp.h pkg/pomp/src/pomp.h www/vignettes/pomp.pdf www/vignettes/pompjss.pdf Log: - improve warnings in 'pomp' when covariate table is supplied but not used - make 'reulermultinom' and 'deulermultinom' R_INLINE Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-13 18:42:28 UTC (rev 1140) +++ pkg/pomp/DESCRIPTION 2015-03-13 18:43:50 UTC (rev 1141) @@ -1,8 +1,8 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.62-8 -Date: 2015-03-06 +Version: 0.62-9 +Date: 2015-03-14 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), person(given=c("Edward","L."),family="Ionides",role=c("aut")), Modified: pkg/pomp/R/pomp.R =================================================================== --- pkg/pomp/R/pomp.R 2015-03-13 18:42:28 UTC (rev 1140) +++ pkg/pomp/R/pomp.R 2015-03-13 18:43:50 UTC (rev 1141) @@ -335,21 +335,24 @@ ) warning("a covariate table has been given, yet the ", sQuote("skeleton")," function does not have ", - sQuote("covars")," as a formal argument",call.=FALSE) + sQuote("covars")," as a formal argument: see ", + sQuote("?pomp"),call.=FALSE) if ( (rmeasure at mode==pompfunmode$Rfun) &&!("covars"%in%names(formals(rmeasure at R.fun))) ) warning("a covariate table has been given, yet the ", sQuote("rmeasure")," function does not have ", - sQuote("covars")," as a formal argument",call.=FALSE) + sQuote("covars")," as a formal argument: see ", + sQuote("?pomp"),call.=FALSE) if ( (dmeasure at mode==pompfunmode$Rfun) &&!("covars"%in%names(formals(dmeasure at R.fun))) ) warning("a covariate table has been given, yet the ", sQuote("dmeasure")," function does not have ", - sQuote("covars")," as a formal argument",call.=FALSE) + sQuote("covars")," as a formal argument: see ", + sQuote("?pomp"),call.=FALSE) } if ((length(tcovar)>0)&&((min(tcovar)>t0)||(max(tcovar)> +<< /Type /ObjStm /Length 4535 /Filter /FlateDecode /N 99 /First 841 >> stream -x??\ks?6??~?m\)???J??ql+????[?[c??f3?Q??u???i??? 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Or????:?;????b^???e??- &[????G??<]?h? +???$$%]?T??+??4t???< +(Cd??$??XPV4( P?????X?!P]XK +V???1?5|?$`|?|????SS???|?????????y4???f?*?? ??L?2W?xf????|?Z>:>z>2=f.?UD?\d??????ez??? +G??,?cE???sL??,:??B???9??v?;??tYO!??=`??x?p??????z??H?????a?????2I??????%H??I??q???8>???*^?~ +-?_? ??]?m?????x?nd/GhG6o???^?|M???AkI??t(5?k??L??1?}5?axe????_???^??????(?$z>[j?,|???,|v$ ??J?{RB?]%0??L ?y???h??B??~fO???;??f?L??0??L??0??p +O]>????>?????l?[????????????S????*f?ggwgog?????7Os?k???Jl??8?l??? ?????4?'1wM%|?????????j??????&8x?(??????????K??-??^??????????b>?g}?,qz/Q~8?? ?????? R=:9Dg?#u.??????:*??;_j???y???L\?O?h9"??-??R?=?C#??,[N?n&???(???? r??? +??E??????z?????N#??/????????jq8;?????iVx +9??xzJYr???Gg?y?2??R2??????.R???????G~7>Y??X%?????Z??tNI?s?g??+~??5U?U9?tl????????U?J?? S??$???4G`}? ?l@?9v?S???????o? ??G?<=??{k???PGC???????Bs?C?????P<???L?(?????8???8o????x'F??8???l????#q"j???O???>??\@??3q???Y=c?O????I?X?s131???B\??L?O???':?|<;??W?e???V?; ?????b?E,??l^?b???X???_???K?[??????$M?>????dtJE?d??3?G:??RTN??=?~:??T??X?`t^_?H?????????J?/p?d??0???>Ku???t?K?g??a=?????]u]?pa???H??????1??IoQ?R?l??~?;? qh????Dc? ?/?AT?u??A?mi&????Cl?n7??H9`?&?????]??????%q???[$?)??bxU:e??*?Lwhc??"?_^?}??1???x??????X??????}2?F3?eW*R??QM +?B??]?*?P%m??{?q?????7?s33? +Stfd???.?x??(?m??e?????????vc?%???0-?4?Dx?wrq???^??????? ?b1????/??Y?)??h.?????O?d?L1Z!?%?????.?j???C?z+i?f+9i?2??????}?2?0???????a?? +G??????? ??`hjwU????6:ma???[??i???7{6?>??-???JCG?tr????????A??u?v????*}??m?nb???E????x?p??`??~??????O?d??`)V?? s?????e???L??8?????????{?????%o?{T??z??\:??????d?=?z?j?ns?\:m- ?'?7??tG????????Q?O?U?\o???m???`?UCuv??????m??5|??????????K{?.???b??_?k????oR?????????)??????????7yMhu??uLLQ?????}sB???$?1E?"????>??Hq? I????C?q??????3?AN?]4>?T#??????HP?LR?O?????&??????*??1~'{??c???A???3?= +?p,E?{??7???"?{??z{?> @@ -44,12 +46,12 @@ - -2015-03-12T07:02:56-04:00 -2015-03-12T07:02:56-04:00 + +2015-03-13T14:35:18-04:00 +2015-03-13T14:35:18-04:00 Raph Levien - -Inconsolata + +Inconsolata @@ -539,15 +541,14 @@ 1010 0 obj << /Filter /FlateDecode /Length 1358 >> stream -x??W[o?6??_???C?????a?: ?\?M??4F???VU??????9?? -ypxxx.????D???>?vs}???Qo?????!n7>?6?ao=??F8?h??6?( h?`?? ??,???z?%??????mHS?N?_?l???????\?)????AHs??l??????'.?z5??F$C%8d4??B????I??2j??8G:?b.a>GS??h??C $????Z?? ???J?T?9"Q?j???JpN?1?{?M?M]?f??e?uw'???>??;??bY?25o????[??z?A?0??[4???Is$? ? =??U?Z ?????7????????!?t-??n?V ?"  -?v??Y??o?&z???? ???bZ.?QF?Z??7???c??~?????7?6P?I -Gj??`?????8-?$-p?1?????\_[?cnC?4???p 6?Q??GQ 6_??gp%?8??$?8M???^ ]??7?B?c?&?????0??^?g?D??)??\? -?????OdH??[??????6???v2????????`!-??JB|C??gmD??FKQ?R?????Q+???[?o?/???^P?^t?sx?S????[???c??????B4???????? ??=N[?kdo?j?c?a?[???Qox?/????r??`J?#o?????F ???e???d???n??(?Aendstream +x??W[o?6??_???C??u?a?: ?\?M??4F???VU??????9?? 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>?[???Qox?/????r??`J?#o?????F D???????d???n??V?Bendstream endobj 1011 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 6295 >> @@ -2621,13 +2622,15 @@ .? ????:??>??xN2!?U?????)??haO?????><{?^?Z?3???LL???W??we[e(p?\V??'R??sU?S??a??2???}a??OF??I]?|??????F)( s??X??L??f_:}???z?iC??k??S?!7t-?>????/????Jh0?????)??????T??endstream endobj 1091 0 obj -<< /Type /XRef /Length 452 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 1092 /ID [<9ac61c30643187d546d94d7bbb69bdf9>] >> +<< /Type /XRef /Length 454 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 1092 /ID [<75a3a5e54542f2f6e35f31314f003565><0bdc932c417f276c8161780ab157fd67>] >> stream -x???AHq?gFwsfW?]JH???? yH??H?AA?B????*??? -?d?B%B?? ??Mu???:?`?T?6??C???>o????g>???/?=/??@ -?ht?=/?Q???#?????2?????B???6??????????M????????z?d^]z??W??????W???U??yet???3??M?yet???k??E??2???VM^=}n^??????q???O???bX????????? ??51????i???W?Q???_???c???????????V1?????a?fXL?O4???=??SdI??????o?????? +N??#V(O???=2?!(?U???3_`[? +?l{)??K?N??6???*~????s?;?,0?????e?=??0??:?????t??7??????x_o$97!O)?A???I{?? d! endstream endobj startxref -278357 +278356 %%EOF Modified: www/vignettes/pompjss.pdf =================================================================== --- www/vignettes/pompjss.pdf 2015-03-13 18:42:28 UTC (rev 1140) +++ www/vignettes/pompjss.pdf 2015-03-13 18:43:50 UTC (rev 1141) @@ -165,7 +165,7 @@ >> stream x??Z[w??~???#?#"X`q???&??(Mm????HB+`????;????j???"??3;;?of??m??b??????m?"JLf???????UP$?~o7????ia????C???????{x???{??????,?????k~]???9S??'???t?w???????t?w??????i$ ]6?????????!?}P;?,???"???Se]??????????t?rlD?4K ?????>??al???B?.?G???????E+?"??? ????? ??d8???a/?QIA????????e?wk?L?w??????$??i????????"g?????Y?^??w???G?:I!?Q?P ??s?%x??Gr?m?o??tG?&L??o?v(?l$%??,??#7E)5?IPTF???K?`???s\??5?8Bp?j?F-????"??"???DSw?|?????Ni-????y??SRO??$7?|?s> zK6&?C`3?]??D5?q? 6?:v/J'(v~F??r; _?ec??Q???4?P???UM?\?oxo??????p????V>?3/|????)?v????523?!k?Cb???{?#??+_?s?5??0?????k?BqE ? -hx?;?> ?????M?5?? ?????M?5??> endobj 219 0 obj << -/Length 5024 +/Length 5021 /Filter /FlateDecode >> stream -x??\??7r?????/7[??? 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?X???????&?i?L?????u????? >??;%S?|/?)?rS?`z?Y???j????2??H???WEZ7??m:??}??????-v\A#8y???9???=??Et\q??m???,???[!?]/?P?????4?H~?r?Hb??0???L!p?T??R]1???5`Lz?E??m?OoH?g\>???m`?$?? +V?s?C? ????}e?u?g??_?? +6M?G?>?*-??@[? + ?B?\ ???G?2??W??a???)?$U?I????&????/?P?%?B{??~???????=??Z@???4?k? +N?x8???6????4,??????$?D????v?4?/???/|??'[?????P\~?$?D????o?=???????Q?4 ?-?M}??0?d?SzwSV!??MV?4????c at Y? ???Y???P at v??H@M?B???M?i5?h]??kHm?:tHD{o8@????C??}v`??????%???q ?????3A?ts?nT?=??????/??v`?????7?{3E?YL6a????????7ad?$n?C?P%x??C??? ?s?}?=??t??A???T??8p?K?BN.? +mzx??a??S2?.?????L????l=???`~?D??WE???6g 3t`g%????4???????&??:???5?6?*as?'?$?/? ?????f??v?X???%??y?h???o? ??#;{~?)??b??n??D?????LD???(??H + )????6??^|??rI&???B???v??J$?$?`??????FA??{*???i?Yo??k?W???8m[?#??k?a/??{ D  +? ?????oP?q?????k????/)??N???????~? +????=?? ??i9?E??z +n????~???3: ??p???8)??1GK???d?|?? ?????????]S?????s??r8=?v1}?t??/ [S??O????~1??????????o???x`???c??J8g????{?T_?2?????????????|?v???tA??-???s??~??????????b?/?)?F????;n???4I??o???z?'?W????y;\?k??x5?3)M?0????X?K?}G????o|?}???x*???G' ??????6?n%????>???b ??=???&????`?%]?R??a@;*??.yC??~?z???isb??t?4?o^H"Z>??k??6???4?0??bm?]8??????? ?1????{??.?Kei +> ???=D??;?|????L???:-0????Cg?|?O~??t?T?-??T*????s^(????J@?????@????$,?x???-TX?S?S???J????6??????#:??[?K1?x? ????l=???n????=b??}???.???,???????w???~b???x???q?m??-????0??WmD&?6^??~????x5?~???Lme?r?Q? z?xU4??h?Oco???? +)??????; H???H????{r???dR??+VJ????0??t?>?}??????U???6b?$???bQ>F/?o??_5rw*A??J??_/??>O???N?hq^{:?e?AC???Nwx??_h????-??[f9?????(pT?lt?nrY???nze (??????S?D?8#???=????2>%V?]?q??-W??7^LVa??L +:!S~:e?A?e?m?y1&??b)M? ??kbl??~U?Ca8~???GY?"?%??????o?Q?y?B('??? +???n??)??? +??????????T??hfasc?s???T`?z?V?n?"W??????? ???5???j???t9??????e?< +#Ov}?C??u???MS??????u Author: kingaa Date: 2015-03-15 17:09:02 +0100 (Sun, 15 Mar 2015) New Revision: 1142 Modified: pkg/pomp/DESCRIPTION pkg/pomp/R/minim.R pkg/pomp/R/nlf.R pkg/pomp/R/spect-match.R pkg/pomp/inst/NEWS pkg/pomp/inst/NEWS.Rd pkg/pomp/tests/bbs-trajmatch.R pkg/pomp/tests/bbs-trajmatch.Rout.save pkg/pomp/tests/ou2-probe.R pkg/pomp/tests/ou2-probe.Rout.save www/content/NEWS.html www/vignettes/pomp.pdf Log: - nloptr and subplex are no longer Dependencies but are Imported instead Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-13 18:43:50 UTC (rev 1141) +++ pkg/pomp/DESCRIPTION 2015-03-15 16:09:02 UTC (rev 1142) @@ -1,8 +1,8 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.62-9 -Date: 2015-03-14 +Version: 0.63-1 +Date: 2015-03-15 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), person(given=c("Edward","L."),family="Ionides",role=c("aut")), @@ -18,8 +18,8 @@ ) URL: http://pomp.r-forge.r-project.org Description: Inference methods for partially observed Markov processes (AKA stochastic dynamical systems, state-space models). -Depends: R(>= 3.0.0), methods, subplex, nloptr -Imports: stats, graphics, mvtnorm, deSolve, coda +Depends: R(>= 3.0.0), methods +Imports: stats, graphics, mvtnorm, deSolve, coda, subplex, nloptr License: GPL(>= 2) LazyData: true MailingList: Subscribe to pomp-announce at r-forge.r-project.org for announcements by going to http://lists.r-forge.r-project.org/mailman/listinfo/pomp-announce. Modified: pkg/pomp/R/minim.R =================================================================== --- pkg/pomp/R/minim.R 2015-03-13 18:43:50 UTC (rev 1141) +++ pkg/pomp/R/minim.R 2015-03-15 16:09:02 UTC (rev 1142) @@ -34,11 +34,11 @@ opts <- list(...) if (method == 'subplex') { - opt <- subplex(par=guess,fn=objfun,control=opts) + opt <- subplex::subplex(par=guess,fn=objfun,control=opts) } else if (method=="sannbox") { opt <- sannbox(par=guess,fn=objfun,control=opts) } else if (method=="nloptr") { - opt <- nloptr(x0=guess,eval_f=objfun,opts=opts) + opt <- nloptr::nloptr(x0=guess,eval_f=objfun,opts=opts) } else { opt <- optim(par=guess,fn=objfun,method=method,control=opts) } Modified: pkg/pomp/R/nlf.R =================================================================== --- pkg/pomp/R/nlf.R 2015-03-13 18:43:50 UTC (rev 1141) +++ pkg/pomp/R/nlf.R 2015-03-15 16:09:02 UTC (rev 1142) @@ -115,26 +115,26 @@ opt <- list(params=params,value=val) } else { if (method == 'subplex') { - opt <- subplex( - par=guess, - fn=nlf.objfun, - object=object, - params=params, - par.index=par.index, - transform=transform, - times=times, - t0=t0, - lags=lags, - period=period, - tensor=tensor, - seed=seed, - transform.data=transform.data, - nrbf=nrbf, - verbose=verbose, - bootstrap=bootstrap, - bootsamp=bootsamp, - control=list(...) - ) + opt <- subplex::subplex( + par=guess, + fn=nlf.objfun, + object=object, + params=params, + par.index=par.index, + transform=transform, + times=times, + t0=t0, + lags=lags, + period=period, + tensor=tensor, + seed=seed, + transform.data=transform.data, + nrbf=nrbf, + verbose=verbose, + bootstrap=bootstrap, + bootsamp=bootsamp, + control=list(...) + ) } else { opt <- optim( par=guess, Modified: pkg/pomp/R/spect-match.R =================================================================== --- pkg/pomp/R/spect-match.R 2015-03-13 18:43:50 UTC (rev 1141) +++ pkg/pomp/R/spect-match.R 2015-03-15 16:09:02 UTC (rev 1142) @@ -174,23 +174,23 @@ msg <- "no optimization performed" } else { if (method == 'subplex') { - opt <- subplex( - par=guess, - fn=obj.fn, - est=par.index, - object=object, - params=params, - vars=vars, - ker=ker, - nsim=nsim, - seed=seed, - transform=transform, - detrend=detrend, - weights=weights, - data.spec=ds, - fail.value=fail.value, - control=list(...) - ) + opt <- subplex::subplex( + par=guess, + fn=obj.fn, + est=par.index, + object=object, + params=params, + vars=vars, + ker=ker, + nsim=nsim, + seed=seed, + transform=transform, + detrend=detrend, + weights=weights, + data.spec=ds, + fail.value=fail.value, + control=list(...) + ) } else { opt <- optim( par=guess, Modified: pkg/pomp/inst/NEWS =================================================================== --- pkg/pomp/inst/NEWS 2015-03-13 18:43:50 UTC (rev 1141) +++ pkg/pomp/inst/NEWS 2015-03-15 16:09:02 UTC (rev 1142) @@ -1,5 +1,11 @@ _N_e_w_s _f_o_r _p_a_c_k_a_g_e '_p_o_m_p' +_C_h_a_n_g_e_s _i_n '_p_o_m_p' _v_e_r_s_i_o_n _0._6_3-_1: + + ??? The optimization packages ???nloptr??? and ???subplex??? are no + longer dependencies of ???pomp??? that will be loaded at the time + ???pomp??? is. Instead, they are imported as needed. + _C_h_a_n_g_e_s _i_n '_p_o_m_p' _v_e_r_s_i_o_n _0._6_2-_2: ??? Bug fix in ???partrans??? when transformations are implemented Modified: pkg/pomp/inst/NEWS.Rd =================================================================== --- pkg/pomp/inst/NEWS.Rd 2015-03-13 18:43:50 UTC (rev 1141) +++ pkg/pomp/inst/NEWS.Rd 2015-03-15 16:09:02 UTC (rev 1142) @@ -1,5 +1,11 @@ \name{NEWS} \title{News for package `pomp'} +\section{Changes in \pkg{pomp} version 0.63-1}{ + \itemize{ + \item The optimization packages \pkg{nloptr} and \pkg{subplex} are no longer dependencies of \pkg{pomp} that will be loaded at the time \pkg{pomp} is. + Instead, they are imported as needed. + } +} \section{Changes in \pkg{pomp} version 0.62-2}{ \itemize{ \item Bug fix in \code{partrans} when transformations are implemented using \code{Csnippet}s. Modified: pkg/pomp/tests/bbs-trajmatch.R =================================================================== --- pkg/pomp/tests/bbs-trajmatch.R 2015-03-13 18:43:50 UTC (rev 1141) +++ pkg/pomp/tests/bbs-trajmatch.R 2015-03-15 16:09:02 UTC (rev 1142) @@ -19,6 +19,7 @@ tmf <- traj.match.objfun(bbs,params=guess,est=est,transform=TRUE,hmax=0.001) +require(subplex) fit <- subplex(fn=tmf,par=log(guess[est]),control=list(reltol=1e-7)) tm2 <- bbs coef(tm2) <- guess Modified: pkg/pomp/tests/bbs-trajmatch.Rout.save =================================================================== --- pkg/pomp/tests/bbs-trajmatch.Rout.save 2015-03-13 18:43:50 UTC (rev 1141) +++ pkg/pomp/tests/bbs-trajmatch.Rout.save 2015-03-15 16:09:02 UTC (rev 1142) @@ -1,6 +1,6 @@ -R version 3.1.2 (2014-10-31) -- "Pumpkin Helmet" -Copyright (C) 2014 The R Foundation for Statistical Computing +R version 3.1.3 (2015-03-09) -- "Smooth Sidewalk" +Copyright (C) 2015 The R Foundation for Statistical Computing Platform: x86_64-unknown-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. @@ -16,8 +16,6 @@ Type 'q()' to quit R. > library(pomp) -Loading required package: subplex -Loading required package: nloptr > > pompExample(bbs) newly created object(s): @@ -54,6 +52,8 @@ > > tmf <- traj.match.objfun(bbs,params=guess,est=est,transform=TRUE,hmax=0.001) > +> require(subplex) +Loading required package: subplex > fit <- subplex(fn=tmf,par=log(guess[est]),control=list(reltol=1e-7)) > tm2 <- bbs > coef(tm2) <- guess @@ -80,4 +80,4 @@ > > proc.time() user system elapsed - 2.480 0.052 2.555 + 2.709 0.041 2.740 Modified: pkg/pomp/tests/ou2-probe.R =================================================================== --- pkg/pomp/tests/ou2-probe.R 2015-03-13 18:43:50 UTC (rev 1141) +++ pkg/pomp/tests/ou2-probe.R 2015-03-15 16:09:02 UTC (rev 1142) @@ -138,6 +138,8 @@ probes=good$probes,nsim=100, seed=349956868L ) + +require(nloptr) fit1 <- nloptr( coef(good,c("alpha.1","alpha.2")), ofun, Modified: pkg/pomp/tests/ou2-probe.Rout.save =================================================================== --- pkg/pomp/tests/ou2-probe.Rout.save 2015-03-13 18:43:50 UTC (rev 1141) +++ pkg/pomp/tests/ou2-probe.Rout.save 2015-03-15 16:09:02 UTC (rev 1142) @@ -1,6 +1,6 @@ -R version 3.1.2 (2014-10-31) -- "Pumpkin Helmet" -Copyright (C) 2014 The R Foundation for Statistical Computing +R version 3.1.3 (2015-03-09) -- "Smooth Sidewalk" +Copyright (C) 2015 The R Foundation for Statistical Computing Platform: x86_64-unknown-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. @@ -16,8 +16,6 @@ Type 'q()' to quit R. > library(pomp) -Loading required package: subplex -Loading required package: nloptr > set.seed(1066L) > > pdf(file="ou2-probe.pdf") @@ -312,6 +310,9 @@ + probes=good$probes,nsim=100, + seed=349956868L + ) +> +> require(nloptr) +Loading required package: nloptr > fit1 <- nloptr( + coef(good,c("alpha.1","alpha.2")), + ofun, @@ -340,4 +341,4 @@ > > proc.time() user system elapsed - 7.892 0.092 8.187 + 9.307 0.094 9.395 Modified: www/content/NEWS.html =================================================================== --- www/content/NEWS.html 2015-03-13 18:43:50 UTC (rev 1141) +++ www/content/NEWS.html 2015-03-15 16:09:02 UTC (rev 1142) @@ -8,6 +8,17 @@

    News for package ‘pomp’

    +

    Changes in pomp version 0.63-1

    + + +
      +

    • The optimization packages nloptr and subplex are no longer dependencies of pomp that will be loaded at the time pomp is. +Instead, they are imported as needed. +

      +
    + + +

    Changes in pomp version 0.62-2

    Modified: www/vignettes/pomp.pdf =================================================================== --- www/vignettes/pomp.pdf 2015-03-13 18:43:50 UTC (rev 1141) +++ www/vignettes/pomp.pdf 2015-03-15 16:09:02 UTC (rev 1142) @@ -17,27 +17,38 @@ V???1?5|?$`|?|????SS???|?????????y4???f?*?? ??L?2W?xf????|?Z>:>z>2=f.?UD?\d??????ez??? -G??,?cE???sL??,:??B???9??v?;??tYO!??=`??x?p??????z??H?????a?????2I??????%H??I??q???8>???*^?~ --?_? ??]?m?????x?nd/GhG6o???^?|M???AkI??t(5?k??L??1?}5?axe????_???^??????(?$z>[j?,|???,|v$ ??J?{RB?]%0??L ?y???h??B??~fO???;??f?L??0??L??0??p -O]>????>?????l?[????????????S????*f?ggwgog?????7Os?k???Jl??8?l??? ?????4?'1wM%|?????????j??????&8x?(??????????K??-??^??????????b>?g}?,qz/Q~8?? ?????? R=:9Dg?#u.??????:*??;_j???y???L\?O?h9"??-??R?=?C#??,[N?n&???(???? r??? -??E??????z?????N#??/????????jq8;?????iVx -9??xzJYr???Gg?y?2??R2??????.R???????G~7>Y??X%?????Z??tNI?s?g??+~??5U?U9?tl????????U?J?? S??$???4G`}? ?l@?9v?S???????o? ??G?<=??{k???PGC???????Bs?C?????P<???L?(?????8???8o????x'F??8???l????#q"j???O???>??\@??3q???Y=c?O????I?X?s131???B\??L?O???':?|<;??W?e???V?; ?????b?E,??l^?b???X???_???K?[??????$M?>????dtJE?d??3?G:??RTN??=?~:??T??X?`t^_?H?????????J?/p?d??0???>Ku???t?K?g??a=?????]u]?pa???H??????1??IoQ?R?l??~?;? qh????Dc? ?/?AT?u??A?mi&????Cl?n7??H9`?&?????]??????%q???[$?)??bxU:e??*?Lwhc??"?_^?}??1???x??????X??????}2?F3?eW*R??QM -?B??]?*?P%m??{?q?????7?s33? -Stfd???.?x??(?m??e?????????vc?%???0-?4?Dx?wrq???^??????? ?b1????/??Y?)??h.?????O?d?L1Z!?%?????.?j???C?z+i?f+9i?2??????}?2?0???????a?? -G??????? ??`hjwU????6:ma???[??i???7{6?>??-???JCG?tr????????A??u?v????*}??m?nb???E????x?p??`??~??????O?d??`)V?? s?????e???L??8?????????{?????%o?{T??z??\:??????d?=?z?j?ns?\:m- ?'?7??tG????????Q?O?U?\o???m???`?UCuv??????m??5|??????????K{?.???b??_?k????oR?????????)??????????7yMhu??uLLQ?????}sB???$?1E?"????>??Hq? I????C?q??????3?AN?]4>?T#??????HP?LR?O?????&??????*??1~'{??c???A???3?= -?p,E?{??7???"?{??z{???*e???????v?????w?????e?y\Oq?????'_?g'???>{??xv6[,??????ee???x9?????t1???{-w??tIJ/?'????}i.6???!??0?|??1?3?c>:?k??I?????z?/?+??d?????e?+??5??h?GS?hU?U?o??e?23?6>6?6????Ty???xDK&x??y?<-sw?25??9??6????j?X3???L?#3?????i?L?jT#0V ??@%KF? ?X???[f??h??????{?'x??2???????`:?-????????F????????#[?1|?|t|?|dz?\d???]??????a???5_?k?'?l?)?U2????????~?%X??94n?????!0?1???3?q,9?????? +?_i*~Ob??J?*S?-?=??7???????i#:?Mp? Q<*???????)????;[./?.?????O??i???|???xY??^??p6?A2??Q%??ztr??8G?\jG??+?7"tT8"?w??'??h?q??x9???rD*??[?/?|{z?F??Y??T?L?_!P???G???_A???b9_?M??x?#?E?FG^b???%&xzt?????)???J????3:??H?d?????x$?'???Q</?+q ^?Cq$??_?[?N??Gq,?g????G?D?"????1?}??'??8g?????z*????1?z??b*fb6???? ??????5Ot.??xv"??f?:?M?|w.bQ????X???????_3??????????w=??K H??}????????6?.fg??t.??????{??ty?5?a}??????v???6 +w??sc?W???d?d????2w&???K}s??"A?_???d???????LgM???? ?n?y>9????2$?y>??4_?s?????{????w????+?m??.???QHp? +^? +?@??2?2h?$^0p? ??e??W???ONj4?-4????Yo?R ?>mH?BQ(% +???fu?*?????P???????????? ???u??f,/J?7a/%?U?&?9??s?MR?c?Xk?w???5*vu`??7M?T?n?3????8w??M?l?L?y?????)i?`?ue?xI?(???c?vpSwj???c?h???)?cC?v?T??V<%?,????v????????O???Vx +?w???????ZxW oj?=-???w???????Y$??R6{??S?^?*?{?cO?Z?w?e???????Q?],?/u???R?#??!??]???,??)[??42 +???3hu?X??(c(???? ??bX]F????@??6q?\?>WN?2?WZ???ZoKo}?=??j??????r??\?1i????S?f^K? +? +???"S?f?m?aZli???"??? ?o?5?o=A??b???>lxX?X?zX?w???`?_???????w?1???x>???V?_9? +?r??ao?}?3jo????z{????(??'?#???J ?I(\c?E?7?7?}?]????.-?W?r????{-)?gH? ?>?hxB?.a 7??F?,???zW? ????R?Eo??[e^'??>b??+ ?#A? ?n`?N??j? +W0?*???*????????TTe??????)??O?xiI?7???t???????]?Kb/g????i%????%??? +???i???IU@??V?S???????"v?"}|> @@ -46,12 +57,12 @@ - -2015-03-13T14:35:18-04:00 -2015-03-13T14:35:18-04:00 + +2015-03-15T12:02:59-04:00 +2015-03-15T12:02:59-04:00 Raph Levien - -Inconsolata + +Inconsolata @@ -541,14 +552,14 @@ 1010 0 obj << /Filter /FlateDecode /Length 1358 >> stream -x??W[o?6??_???C??u?a?: ?\?M??4F???VU??????9?? -ypxxx.????D???>?vs}???Qo?????!n7>?6?ao=X@#??4 ?w?4f8?H?d9?y????vK"E??'~??&v??_?l???????\$ ???4/??f8#?? -W?=?g.???j F?H2?b8?4??B?f8OX?3??>?~?18G:?b.a>G?C ????&$????Z?? ???J?T?9"Q?j???b8??????????x3????uw'???>??;??bY?25o????[??z?A?0??Y4???I2$?KNs?0?V?Jh-?z??j?l?k?c[?z? ?k??ug????,?????>???-?D?????"-??? a????}CJ?????7;???~?n%??p?V_??|vBS'E???4?#poL?????;V?6?K??; -?p`? ?J~????`??|yW?G?Y0Fq????^ ]??7?B?c?0Lm??V?? -s/??m?]??mH.?l?d?'? -?O?-z????CY?s;??g?p?x[????jx%!??y????6??W?%??@?P??u???????-?7??H|/(q/:??9????02?{s???vL??C??Q???W3v?T? $?B??????F?F?9??3vU?n{??Z?q?i?EZL?TEG?????M9jL'U;?r?e???,`??/????8d?@qWW??kb??D????8?9????,???J??? :??.+?,guk -2z](?^7uw??t? ??????O??rzSd?L+!?:y?i?^?v??S?9???? ??y\?AC??3z?Uy??;J(}????|????V?,?? h?6????L$?|?W ?o????Z??Huw'?/????o?G?4??@?`F???????y?? ?JigP?? -(=????S#T{j?????R6s?1*u??:Am?fJ???g???~)??s???Z?v?Q[S??>)^?3?????????^?????i<2??f??????%?'ad?,??sRK?$?/?c??&-?u?3???????????i??Ec???L?????-???W???!???_?-u[?WF??.[mZn???3??'w9M?n?\/5o?)h?)?_??k???,&?d????KBY?,?^/?_???&\%?u?? >?[???Qox?/????r??`J?#o?????F D???????d???n??V?Bendstream +x??W???6????[?"????K?M??H?????K?@)??*?D???u??CR??]5h?^????9sh +"L?????U???????7Qp?|?{?U??7I@#??????]%??g$`Y?i??v????GQ?x????6????W/??????_??4 ?Q?0?qL?"i?3????P??C??z??4;??^j?,(S?VS@?X!D???,&?d6O?A/ e?d??z?`?????a??????????B{0??{?Z?=?6????j?9X????CB)z?-?:endstream endobj 1011 0 obj << /Filter /FlateDecode /Subtype /Type1C /Length 6295 >> @@ -846,7 +857,7 @@ x??ZKs?6????B???1@`??0??!??lW?a???,&???8?????d??????Eh4>|h???/?H.b??????/6zq7\??????$?.??r???zHiy?g*[\o?p?*?b?o!?{?$[)?L??????w??j_??w???W?';?C??D2?GC????WI?E&S??2?z??????X,W*?????-????q???=??????=??.V2?TjX????1?????O6???X??-?sQ???tS9????DJ'?X??*-?????????9M?? xs???E 6?Al"~l??]?S?t*#?H??i*y??%dT+J????4 MD??skDY4?o???????OWL}???E?4??)???VEY?.?TEI?L$??:??H?l.??u?????PQ?(?O?I#u?^??????&yIa??}w[?v?Xn??i??A?[???????Sq??????y?-??p??s Mj??R??}1a?q(??????hgX?D????????2???= ???????b?L? @@ -863,7 +874,7 @@ I?aRJ?/I3?Y????;?Wc?Z?5???????G6U??q??O!????~nrb??2?G????Q???? '????Hs%????B?H9?????J1}$??,?b]?pA??;??m?T??A?*??\???0?????|5#???/m$??@??M]?y???q??LN2p,O?<{????. ?%ofP?/??? f???v.??G?w?P???`????? ?,?&-??Xg?2X?o?3V???Di|???@????`?T??$??9?L??R1????$'??A?(t??'??Y????????6{?????????6WV>?-kb????8 5????.????*RS`UxE?*%????C1}pvB???#??-:?Z?w?f?????j?s2q? -w??8????C]?^??l?Z???9P?9]??W ??qC@??,t????:?{y????$8d??on??72?C`?/?R?|}?z????F~?r??@PC?}???nN?/?q?? 8? ?? ??Sf???r??Km?9F}?M????sO|Iy!?QR?@???????"?c?!s??=e2?]?1&K?endstream +w??8????C]?^??l?Z???9P?9]??W ??qC@??,t????:?{y????$8d??on??72?C`?/?R?|}?z????F~?r??@PC?}???nN?/?q?? 8? ?? ??Sf???r??Km?9F}?M????sO|Iy!?QR?@???????"?c?!s??=e2?]?gK?endstream endobj 1019 0 obj << /Filter /FlateDecode /Length 305 >> @@ -2622,7 +2633,7 @@ .? ????:??>??xN2!?U?????)??haO?????><{?^?Z?3???LL???W??we[e(p?\V??'R??sU?S??a??2???}a??OF??I]?|??????F)( s??X??L??f_:}???z?iC??k??S?!7t-?>????/????Jh0?????)??????T??endstream endobj 1091 0 obj -<< /Type /XRef /Length 454 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 1092 /ID [<75a3a5e54542f2f6e35f31314f003565><0bdc932c417f276c8161780ab157fd67>] >> +<< /Type /XRef /Length 454 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 1092 /ID [<3c5925c65ea90cd4d6649bd6a1c89527><1d9ea8e177b316aaf07480aab56e1ecf>] >> stream x???OHa?g???Yu?E? ?(4???????!x?P??@?C *??? ?X*Q???m?i?J=????? BA From noreply at r-forge.r-project.org Mon Mar 16 13:21:51 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Mon, 16 Mar 2015 13:21:51 +0100 (CET) Subject: [Pomp-commits] r1143 - in pkg/pomp: . R Message-ID: <20150316122151.EF9D4184FA3@r-forge.r-project.org> Author: kingaa Date: 2015-03-16 13:21:51 +0100 (Mon, 16 Mar 2015) New Revision: 1143 Modified: pkg/pomp/DESCRIPTION pkg/pomp/R/builder.R Log: - fix some problems with rendering from templates Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-15 16:09:02 UTC (rev 1142) +++ pkg/pomp/DESCRIPTION 2015-03-16 12:21:51 UTC (rev 1143) @@ -1,8 +1,8 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.63-1 -Date: 2015-03-15 +Version: 0.63-2 +Date: 2015-03-16 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), person(given=c("Edward","L."),family="Ionides",role=c("aut")), Modified: pkg/pomp/R/builder.R =================================================================== --- pkg/pomp/R/builder.R 2015-03-15 16:09:02 UTC (rev 1142) +++ pkg/pomp/R/builder.R 2015-03-16 12:21:51 UTC (rev 1143) @@ -21,7 +21,7 @@ if (.Platform$OS.type=="windows") { stem <- gsub("\\","/",stem,fixed=TRUE) } - modelfile <- paste0(stem,".c") + modelfile <- paste0(stem,".c") solib <- paste0(stem,.Platform$dynlib.ext) if (.Platform$OS.type=="unix") { @@ -29,9 +29,9 @@ } else { pompheader <- system.file("include/pomp.h",package="pomp") } - + out <- file(description=modelfile,open="w") - + cat(file=out,render(header$file,name=name,pompheader=pompheader)) for (f in utility.fns) { @@ -42,24 +42,24 @@ ## variable/parameter/observations definitions for (v in seq_along(paramnames)) { - cat(file=out,render(define$var,variable=paramnames[v],ptr='__p',ilist='__parindex',index=v-1)) + cat(file=out,render(define$var,variable=paramnames[v],ptr='__p',ilist='__parindex',index=as.integer(v-1))) } for (v in seq_along(statenames)) { - cat(file=out,render(define$var,variable=statenames[v],ptr='__x',ilist='__stateindex',index=v-1)) + cat(file=out,render(define$var,variable=statenames[v],ptr='__x',ilist='__stateindex',index=as.integer(v-1))) } for (v in seq_along(covarnames)) { - cat(file=out,render(define$var,variable=covarnames[v],ptr='__covars',ilist='__covindex',index=v-1)) + cat(file=out,render(define$var,variable=covarnames[v],ptr='__covars',ilist='__covindex',index=as.integer(v-1))) } for (v in seq_along(obsnames)) { - cat(file=out,render(define$var,variable=obsnames[v],ptr='__y',ilist='__obsindex',index=v-1)) + cat(file=out,render(define$var,variable=obsnames[v],ptr='__y',ilist='__obsindex',index=as.integer(v-1))) } for (v in seq_along(statenames)) { - cat(file=out,render(define$var,variable=paste0("D",statenames[v]),ptr='__f',ilist='__stateindex',index=v-1)) + cat(file=out,render(define$var,variable=paste0("D",statenames[v]),ptr='__f',ilist='__stateindex',index=as.integer(v-1))) } for (v in seq_along(paramnames)) { - cat(file=out,render(define$var,variable=paste0("T",paramnames[v]),ptr='__pt',ilist='__parindex',index=v-1)) + cat(file=out,render(define$var,variable=paste0("T",paramnames[v]),ptr='__pt',ilist='__parindex',index=as.integer(v-1))) } - cat(file=out,render(define$var.alt,variable="lik",ptr='__lik',index=0)) + cat(file=out,render(define$var.alt,variable="lik",ptr='__lik',index=0L)) ## list of functions to register registry <- c("load_stack_incr","load_stack_decr") @@ -193,6 +193,7 @@ cleanForC <- function (text) { text <- as.character(text) text <- gsub("\\.","_",text) + text <- gsub("-","_",text) text } @@ -204,7 +205,7 @@ short <- which(n==1) n <- max(n) for (i in short) vars[[i]] <- rep(vars[[i]],n) - + retval <- vector(mode="list",length=n) for (i in seq_len(n)) { tpl <- template @@ -226,7 +227,7 @@ parameter.transform, parameter.inv.transform, rprior, dprior, globals, ..., save = FALSE) { - + if (!is.data.frame(data)) stop(sQuote("data")," must be a data-frame") obsnames <- names(data) obsnames <- setdiff(obsnames,times) From noreply at r-forge.r-project.org Mon Mar 16 13:22:00 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Mon, 16 Mar 2015 13:22:00 +0100 (CET) Subject: [Pomp-commits] r1144 - www/vignettes Message-ID: <20150316122200.13419184FA3@r-forge.r-project.org> Author: kingaa Date: 2015-03-16 13:21:59 +0100 (Mon, 16 Mar 2015) New Revision: 1144 Modified: www/vignettes/getting_started.R www/vignettes/getting_started.Rmd www/vignettes/getting_started.html www/vignettes/pomp.pdf Log: - more work on "getting started" vignette Modified: www/vignettes/getting_started.R =================================================================== --- www/vignettes/getting_started.R 2015-03-16 12:21:51 UTC (rev 1143) +++ www/vignettes/getting_started.R 2015-03-16 12:21:59 UTC (rev 1144) @@ -25,7 +25,6 @@ ) ## ----prelims,echo=F,cache=F---------------------------------------------- -set.seed(594709947L) require(ggplot2) require(plyr) require(reshape2) @@ -40,6 +39,15 @@ scipen=5 ) +## ----parallel,include=FALSE,cache=FALSE---------------------------------- +require(foreach) +require(doMC) +options(cores=5) +registerDoMC() +set.seed(594709947L,kind="L'Ecuyer") +mcopts <- list(set.seed=TRUE) +paropts <- list(.options.multicore=mcopts) + ## ----eval=FALSE---------------------------------------------------------- ## install.packages("pomp",repos="http://R-Forge.R-Project.org") @@ -210,12 +218,45 @@ tm <- traj.match(parus,start=c(r=1,K=200,phi=1,N.0=200,sigma=0.5), est=c("r","K","phi"),transform=TRUE) signif(coef(tm),3) +logLik(tm) ## ----parus-tm-sim1,cache=FALSE------------------------------------------- coef(tm,"sigma") <- 0 -sim <- simulate(tm,nsim=10,as.data.frame=TRUE,include.data=TRUE) -ggplot(data=sim,mapping=aes(x=time,y=pop,group=sim,alpha=(sim=="data")))+ +sim1 <- simulate(tm,nsim=10,as.data.frame=TRUE,include.data=TRUE) +ggplot(data=sim1,mapping=aes(x=time,y=pop,group=sim,alpha=(sim=="data")))+ scale_alpha_manual(name="",values=c(`TRUE`=1,`FALSE`=0.2), labels=c(`FALSE`="simulation",`TRUE`="data"))+ geom_line() +## ----parus-mif,cache=TRUE------------------------------------------------ +mf <- mif(parus,Nmif=50,Np=1000,method="mif2",cooling.fraction=0.8, + rw.sd=c(r=0.02,K=0.02,phi=0.02,sigma=0.02),transform=TRUE) +mf <- mif(mf) +mle <- coef(mf); mle +logmeanexp(replicate(5,logLik(pfilter(mf))),se=TRUE) +sim2 <- simulate(mf,nsim=10,as.data.frame=TRUE,include.data=TRUE) +ggplot(data=sim2,mapping=aes(x=time,y=pop,group=sim,alpha=(sim=="data")))+ + scale_alpha_manual(name="",values=c(`TRUE`=1,`FALSE`=0.2), + labels=c(`FALSE`="simulation",`TRUE`="data"))+ + geom_line() + +## ----parus-pmcmc,cache=TRUE---------------------------------------------- +dprior <- Csnippet(" + lik = dunif(r,0,5,1)+dunif(K,100,800,1)+dunif(phi,0,2,1)+ + dunif(sigma,0,2,1); + lik = (give_log) ? lik : exp(lik); + ") +parus <- pomp(parus,dprior=dprior,paramnames=c("r","K","phi","sigma")) +pchs <- foreach (i=1:5,.combine=c, + .options.multicore=mcopts) %dopar% { + pmcmc(parus,Nmcmc=1000,Np=100,start=mle, + proposal=mvn.diag.rw(c(r=0.02,K=0.02,phi=0.02,sigma=0.02))) + } +traces <- conv.rec(pchs,c("r","K","phi")) +require(coda) +plot(traces[,"r"]) +plot(traces[,"K"]) +plot(traces[,"phi"]) +gelman.plot(traces) +gelman.diag(traces) + Modified: www/vignettes/getting_started.Rmd =================================================================== --- www/vignettes/getting_started.Rmd 2015-03-16 12:21:51 UTC (rev 1143) +++ www/vignettes/getting_started.Rmd 2015-03-16 12:21:59 UTC (rev 1144) @@ -44,7 +44,6 @@ ```{r prelims,echo=F,cache=F} -set.seed(594709947L) require(ggplot2) require(plyr) require(reshape2) @@ -59,6 +58,15 @@ scipen=5 ) ``` +```{r parallel,include=FALSE,cache=FALSE} +require(foreach) +require(doMC) +options(cores=5) +registerDoMC() +set.seed(594709947L,kind="L'Ecuyer") +mcopts <- list(set.seed=TRUE) +paropts <- list(.options.multicore=mcopts) +``` ## Introduction @@ -426,13 +434,14 @@ tm <- traj.match(parus,start=c(r=1,K=200,phi=1,N.0=200,sigma=0.5), est=c("r","K","phi"),transform=TRUE) signif(coef(tm),3) +logLik(tm) ``` We can simulate the fitted model and compare it against the data. ```{r parus-tm-sim1,cache=FALSE} coef(tm,"sigma") <- 0 -sim <- simulate(tm,nsim=10,as.data.frame=TRUE,include.data=TRUE) -ggplot(data=sim,mapping=aes(x=time,y=pop,group=sim,alpha=(sim=="data")))+ +sim1 <- simulate(tm,nsim=10,as.data.frame=TRUE,include.data=TRUE) +ggplot(data=sim1,mapping=aes(x=time,y=pop,group=sim,alpha=(sim=="data")))+ scale_alpha_manual(name="",values=c(`TRUE`=1,`FALSE`=0.2), labels=c(`FALSE`="simulation",`TRUE`="data"))+ geom_line() @@ -440,8 +449,49 @@ ## Maximizing the likelihood by iterated filtering +Iterated filtering [@Ionides2015; @Ionides2006] is a method for maximizing the likelihood by repeatedly applying a particle filter. The following codes apply the IF2 algorithm [@Ionides2015]. +```{r parus-mif,cache=TRUE} +mf <- mif(parus,Nmif=50,Np=1000,method="mif2",cooling.fraction=0.8, + rw.sd=c(r=0.02,K=0.02,phi=0.02,sigma=0.02),transform=TRUE) +mf <- mif(mf) +mle <- coef(mf); mle +logmeanexp(replicate(5,logLik(pfilter(mf))),se=TRUE) +sim2 <- simulate(mf,nsim=10,as.data.frame=TRUE,include.data=TRUE) +ggplot(data=sim2,mapping=aes(x=time,y=pop,group=sim,alpha=(sim=="data")))+ + scale_alpha_manual(name="",values=c(`TRUE`=1,`FALSE`=0.2), + labels=c(`FALSE`="simulation",`TRUE`="data"))+ + geom_line() +``` + +The first command runs 50 iterations of the algorithm; the second re-runs the algorithm from where the first run ended up. +The next line extracts and displays the MLE. +The fourth command runs 5 replicate particle filters to compute the log likelihood at the estimated parameters and averages these appropriately to get an estimate of this likelihood and of the standard Monte Carlo error. +Finally, the above plots the data and 10 simulated realizations of the model process on the same axes. + ## Sampling the posterior using particle Markov chain Monte Carlo +The following codes cause 5 parallel pMCMC chains to be run, beginning at the MLE obtained above. +```{r parus-pmcmc,cache=TRUE} +dprior <- Csnippet(" + lik = dunif(r,0,5,1)+dunif(K,100,800,1)+dunif(phi,0,2,1)+ + dunif(sigma,0,2,1); + lik = (give_log) ? lik : exp(lik); + ") +parus <- pomp(parus,dprior=dprior,paramnames=c("r","K","phi","sigma")) +pchs <- foreach (i=1:5,.combine=c, + .options.multicore=mcopts) %dopar% { + pmcmc(parus,Nmcmc=1000,Np=100,start=mle, + proposal=mvn.diag.rw(c(r=0.02,K=0.02,phi=0.02,sigma=0.02))) + } +traces <- conv.rec(pchs,c("r","K","phi")) +require(coda) +plot(traces[,"r"]) +plot(traces[,"K"]) +plot(traces[,"phi"]) +gelman.plot(traces) +gelman.diag(traces) +``` + ## Model checking using probes ## References Modified: www/vignettes/getting_started.html =================================================================== --- www/vignettes/getting_started.html 2015-03-16 12:21:51 UTC (rev 1143) +++ www/vignettes/getting_started.html 2015-03-16 12:21:59 UTC (rev 1144) @@ -90,7 +90,7 @@

    Licensed under the Creative Commons attribution-noncommercial license. Please share and remix noncommercially, mentioning its origin.
    CC-BY_NC

    -

    This document was produced using pomp version 0.62.8.

    +

    This document was produced using pomp version 0.63.1.

    Introduction

    This tutorial aims to help you get started using pomp as a suite of tools for analysis of time series data based on dynamical systems models. First, we give some conceptual background regarding the class of models?partially observed Markov processes?that pomp handles. We then discuss some preliminaries: installing the package and so on. Next, using a basic question about ecological population regulation as an example, we load some data and implement some models as R objects of class pomp. Finally, we illustrate some of the package?s capabilities by using its algorithms to fit and compare the models using various inference methods.

    @@ -174,7 +174,7 @@ geom_line()+geom_point()+ expand_limits(y=0)+ theme_classic() [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1144 From noreply at r-forge.r-project.org Mon Mar 23 13:59:09 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Mon, 23 Mar 2015 13:59:09 +0100 (CET) Subject: [Pomp-commits] r1145 - in www: content vignettes Message-ID: <20150323125910.06664187296@r-forge.r-project.org> Author: kingaa Date: 2015-03-23 13:59:09 +0100 (Mon, 23 Mar 2015) New Revision: 1145 Added: www/vignettes/mif2.R www/vignettes/mif2.Rmd www/vignettes/mif2.html Modified: www/content/vignettes.htm www/vignettes/Makefile www/vignettes/pomp.pdf Log: - add mif2 vignette Modified: www/content/vignettes.htm =================================================================== --- www/content/vignettes.htm 2015-03-16 12:21:59 UTC (rev 1144) +++ www/content/vignettes.htm 2015-03-23 12:59:09 UTC (rev 1145) @@ -11,6 +11,11 @@
    + + + + + Modified: www/vignettes/Makefile =================================================================== --- www/vignettes/Makefile 2015-03-16 12:21:59 UTC (rev 1144) +++ www/vignettes/Makefile 2015-03-23 12:59:09 UTC (rev 1145) @@ -1,5 +1,5 @@ RSCRIPT = $(R_HOME)/bin/Rscript --vanilla -REXE = $(R_HOME)/bin/R --vanilla +REXE = $(R_HOME)/bin/R --vanilla --slave LATEX = latex BIBTEX = bibtex PDFLATEX = pdflatex Added: www/vignettes/mif2.R =================================================================== --- www/vignettes/mif2.R (rev 0) +++ www/vignettes/mif2.R 2015-03-23 12:59:09 UTC (rev 1145) @@ -0,0 +1,115 @@ +## ----options,include=FALSE,cache=FALSE----------------------------------- +library(knitr) +prefix <- "mif2" +opts_chunk$set( + progress=TRUE, + prompt=FALSE,tidy=FALSE,highlight=TRUE, + strip.white=TRUE, + warning=FALSE, + message=FALSE, + error=FALSE, + echo=TRUE, + cache=TRUE, + results='markup', + fig.show='asis', + size='small', + fig.lp="fig:", + fig.path=paste0("figure/",prefix,"-"), + cache.path=paste0("cache/",prefix,"-"), + fig.pos="h!", + fig.align='center', + fig.height=4,fig.width=6.83, + dpi=300, + dev='png', + dev.args=list(bg='transparent') + ) +require(ggplot2) +require(plyr) +require(reshape2) +require(magrittr) +require(pomp) +theme_set(theme_bw()) +stopifnot(packageVersion("pomp")>="0.63-1") +options( + keep.source=TRUE, + stringsAsFactors=FALSE, + encoding="UTF-8", + scipen=5, + cores=5 + ) + +## ----gompertz-init,cache=FALSE------------------------------------------- +require(pomp) +pompExample(gompertz) +theta <- coef(gompertz) +theta.true <- theta + +## ----gompertz-multi-mif2-eval,results='hide'----------------------------- +require(foreach) +require(doMC) +registerDoMC() + +save.seed <- .Random.seed +set.seed(334388458L,kind="L'Ecuyer") + +estpars <- c("r","sigma","tau") +mf <- foreach(i=1:10, + .inorder=FALSE, + .options.multicore=list(set.seed=TRUE) + ) %dopar% + { + theta.guess <- theta.true + theta.guess[estpars] <- rlnorm( + n=length(estpars), + meanlog=log(theta.guess[estpars]), + sdlog=1 + ) + m1 <- mif( + gompertz, + Nmif=50, + method="mif2", + start=theta.guess, + transform=TRUE, + rw.sd=c(r=0.02,sigma=0.02,tau=0.05), + Np=2000, + var.factor=2, + cooling.type="hyperbolic", + cooling.fraction=0.95 + ) + m1 <- continue(m1,Nmif=50,cooling.fraction=0.8) + m1 <- continue(m1,Nmif=50,cooling.fraction=0.6) + m1 <- continue(m1,Nmif=50,cooling.fraction=0.2) + ll <- replicate(n=10,logLik(pfilter(m1,Np=10000))) + list(mif=m1,ll=ll) + } + +rbind( + mle=c(signif(theta.mif[estpars],3),loglik=round(loglik.mif,2)), + truth=c(signif(theta.true[estpars],3),loglik=round(loglik.true,2)) + ) -> results.table + +## ----gompertz-post-mif2-------------------------------------------------- +theta.true <- coef(gompertz) +loglik.true <- replicate(n=10,logLik(pfilter(gompertz,Np=10000))) +loglik.true <- logmeanexp(loglik.true,se=TRUE) +theta.mif <- t(sapply(mf,function(x)coef(x$mif))) +loglik.mif <- t(sapply(mf,function(x)logmeanexp(x$ll,se=TRUE))) +best <- which.max(loglik.mif[,1]) +theta.mif <- theta.mif[best,] +loglik.mif <- loglik.mif[best,] + +## ----mif2-plot,echo=FALSE,cache=FALSE------------------------------------ +op <- par(mfrow=c(4,1),mar=c(3,3,0,0),mgp=c(2,1,0),bty='l') +loglik <- sapply(mf,function(x)conv.rec(x$mif,"loglik")) +log.r <- sapply(mf,function(x)conv.rec(x$mif,"r")) +log.sigma <- sapply(mf,function(x)conv.rec(x$mif,"sigma")) +log.tau <- sapply(mf,function(x)conv.rec(x$mif,"tau")) +matplot(loglik,type='l',lty=1,xlab="",ylab=expression(log~L),xaxt='n',ylim=max(loglik,na.rm=T)+c(-12,3)) +matplot(log.r,type='l',lty=1,xlab="",ylab=expression(log~r),xaxt='n') +matplot(log.sigma,type='l',lty=1,xlab="",ylab=expression(log~sigma),xaxt='n') +matplot(log.tau,type='l',lty=1,xlab="MIF iteration",ylab=expression(log~tau)) +par(op) + +## ----first-mif-results-table,echo=FALSE,cache=FALSE---------------------- +print(results.table) + Added: www/vignettes/mif2.Rmd =================================================================== --- www/vignettes/mif2.Rmd (rev 0) +++ www/vignettes/mif2.Rmd 2015-03-23 12:59:09 UTC (rev 1145) @@ -0,0 +1,152 @@ +--- +title: "An IF2 example" +author: "Aaron A. King" +output: + html_document: + theme: flatly + toc: yes +bibliography: pomp.bib +csl: ecology.csl +--- + +```{r options,include=FALSE,cache=FALSE} +library(knitr) +prefix <- "mif2" +opts_chunk$set( + progress=TRUE, + prompt=FALSE,tidy=FALSE,highlight=TRUE, + strip.white=TRUE, + warning=FALSE, + message=FALSE, + error=FALSE, + echo=TRUE, + cache=TRUE, + results='markup', + fig.show='asis', + size='small', + fig.lp="fig:", + fig.path=paste0("figure/",prefix,"-"), + cache.path=paste0("cache/",prefix,"-"), + fig.pos="h!", + fig.align='center', + fig.height=4,fig.width=6.83, + dpi=300, + dev='png', + dev.args=list(bg='transparent') + ) +require(ggplot2) +require(plyr) +require(reshape2) +require(magrittr) +require(pomp) +theme_set(theme_bw()) +stopifnot(packageVersion("pomp")>="0.63-1") +options( + keep.source=TRUE, + stringsAsFactors=FALSE, + encoding="UTF-8", + scipen=5, + cores=5 + ) +``` + +Iterated filtering is a technique for maximizing the likelihood obtained by filtering. +In `pomp`, it is the particle filter that is iterated. +Iterated filtering is implemented in the `mif` function. + at Ionides2015 describe an improvement on the original [@Ionides2006] algorithm. +This "IF2" algorithm is currently implemented by setting the `method="mif2"` option in `mif`. + +Let's use iterated filtering to obtain an approximate MLE for the data in the Gompertz model example provided with `pomp`. +We'll initialize the algorithm at several starting points around `theta.true` and just estimate the parameters $r$, $\tau$, and $\sigma$: +```{r gompertz-init,cache=FALSE} +require(pomp) +pompExample(gompertz) +theta <- coef(gompertz) +theta.true <- theta +``` + +Note that we've set `transform=TRUE` in the above. +This means that the likelihood maximization is done on the estimation scale (see the section above on Parameter Transformations). + +```{r gompertz-multi-mif2-eval,results='hide'} +require(foreach) +require(doMC) +registerDoMC() + +save.seed <- .Random.seed +set.seed(334388458L,kind="L'Ecuyer") + +estpars <- c("r","sigma","tau") +mf <- foreach(i=1:10, + .inorder=FALSE, + .options.multicore=list(set.seed=TRUE) + ) %dopar% + { + theta.guess <- theta.true + theta.guess[estpars] <- rlnorm( + n=length(estpars), + meanlog=log(theta.guess[estpars]), + sdlog=1 + ) + m1 <- mif( + gompertz, + Nmif=50, + method="mif2", + start=theta.guess, + transform=TRUE, + rw.sd=c(r=0.02,sigma=0.02,tau=0.05), + Np=2000, + var.factor=2, + cooling.type="hyperbolic", + cooling.fraction=0.95 + ) + m1 <- continue(m1,Nmif=50,cooling.fraction=0.8) + m1 <- continue(m1,Nmif=50,cooling.fraction=0.6) + m1 <- continue(m1,Nmif=50,cooling.fraction=0.2) + ll <- replicate(n=10,logLik(pfilter(m1,Np=10000))) + list(mif=m1,ll=ll) + } +``` +```{r gompertz-post-mif2} +loglik.true <- replicate(n=10,logLik(pfilter(gompertz,Np=10000))) +loglik.true <- logmeanexp(loglik.true,se=TRUE) +theta.mif <- t(sapply(mf,function(x)coef(x$mif))) +loglik.mif <- t(sapply(mf,function(x)logmeanexp(x$ll,se=TRUE))) +best <- which.max(loglik.mif[,1]) +theta.mif <- theta.mif[best,] +loglik.mif <- loglik.mif[best,] +rbind( + mle=c(signif(theta.mif[estpars],3),loglik=round(loglik.mif,2)), + truth=c(signif(theta.true[estpars],3),loglik=round(loglik.true,2)) + ) -> results.table +``` + +Each of the `r length(mf)` `mif` runs ends up at a different place. +In this case (but by no means in every case), we can average across these parameter estimates to get an approximate maximum likelihood estimate. +We'll evaluate the likelihood several times at this estimate to get an idea of the Monte Carlo error in our likelihood estimate. +The particle filter produces an unbiased estimate of the likelihood; +therefore, we'll average the likelihoods, not the log likelihoods. + + +Convergence plots can be used to help diagnose convergence of the iterated filtering algorithm. +The following shows part of the output of `plot(mf)`. + +```{r mif2-plot,echo=FALSE,cache=FALSE,fig.height=6} +op <- par(mfrow=c(4,1),mar=c(3,3,0,0),mgp=c(2,1,0),bty='l') +loglik <- sapply(mf,function(x)conv.rec(x$mif,"loglik")) +log.r <- sapply(mf,function(x)conv.rec(x$mif,"r")) +log.sigma <- sapply(mf,function(x)conv.rec(x$mif,"sigma")) +log.tau <- sapply(mf,function(x)conv.rec(x$mif,"tau")) +matplot(loglik,type='l',lty=1,xlab="",ylab=expression(log~L),xaxt='n',ylim=max(loglik,na.rm=T)+c(-12,3)) +matplot(log.r,type='l',lty=1,xlab="",ylab=expression(log~r),xaxt='n') +matplot(log.sigma,type='l',lty=1,xlab="",ylab=expression(log~sigma),xaxt='n') +matplot(log.tau,type='l',lty=1,xlab="MIF iteration",ylab=expression(log~tau)) +par(op) +``` + +Here is a summary of the results. +```{r first-mif-results-table,echo=FALSE,cache=FALSE} +print(results.table) +``` + +## References Added: www/vignettes/mif2.html =================================================================== --- www/vignettes/mif2.html (rev 0) +++ www/vignettes/mif2.html 2015-03-23 12:59:09 UTC (rev 1145) @@ -0,0 +1,162 @@ + + + + + + + + + + + + + +An IF2 example + [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1145 From noreply at r-forge.r-project.org Mon Mar 23 13:59:14 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Mon, 23 Mar 2015 13:59:14 +0100 (CET) Subject: [Pomp-commits] r1146 - pkg/pomp pkg/pomp/man www/vignettes Message-ID: <20150323125914.81391187296@r-forge.r-project.org> Author: kingaa Date: 2015-03-23 13:59:14 +0100 (Mon, 23 Mar 2015) New Revision: 1146 Modified: pkg/pomp/DESCRIPTION pkg/pomp/man/csnippet.Rd www/vignettes/pomp.pdf Log: - document Csnippets for rprior and dprior Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-23 12:59:09 UTC (rev 1145) +++ pkg/pomp/DESCRIPTION 2015-03-23 12:59:14 UTC (rev 1146) @@ -1,8 +1,8 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.63-2 -Date: 2015-03-16 +Version: 0.63-3 +Date: 2015-03-23 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), person(given=c("Edward","L."),family="Ionides",role=c("aut")), Modified: pkg/pomp/man/csnippet.Rd =================================================================== --- pkg/pomp/man/csnippet.Rd 2015-03-23 12:59:09 UTC (rev 1145) +++ pkg/pomp/man/csnippet.Rd 2015-03-23 12:59:14 UTC (rev 1146) @@ -50,7 +50,8 @@ } \section{Rules for writing \code{dmeasure} snippets}{ \enumerate{ - \item The goal of such a snippet is to fill the \code{lik} variable with the likelihood of the data given the state. Alternatively, if \code{give_log=1}, \code{lik} should be filled with the log likelihood. + \item The goal of such a snippet is to fill the \code{lik} variable with the likelihood of the data given the state. + Alternatively, if \code{give_log=1}, \code{lik} should be filled with the log likelihood. \item In addition to the states, parameters, covariates (if any), and observables, the variable \code{t}, containing the time of the observation, will be defined in the context in which the snippet is executed. } } @@ -68,6 +69,24 @@ \item As with the other C snippets, all states, parameters and covariates, as well as the current time, \code{t}, will be defined in the context within which the snippet is executed. } } +\section{Rules for writing \code{rprior} snippets}{ + \enumerate{ + \item The goal of such a snippet is the replacement of parameters with values drawn from the prior distribution. + \item Within the context in which the snippet will be evaluated, only the parameters will be defined. + \item Hyperparameters can be included in the ordinary parameter list. + Obviously, hyperparameters should not be replaced with random draws. + } +} +\section{Rules for writing \code{dprior} snippets}{ + \enumerate{ + \item The goal of such a snippet is computation of the prior probability density, or the log of same, at a given point in parameter space. + This scalar value should be returned in the variable \code{lik}. + When \code{give_log=1}, the user should return the log of the prior probability density. + \item Within the context in which the snippet will be evaluated, only the parameters and \code{give_log} will be defined. + \item Hyperparameters can be included in the ordinary parameter list. + Obviously, hyperparameters should not be replaced with random draws. + } +} \section{Rules for writing parameter transformation snippets}{ \enumerate{ \item The parameter transformation mapping a parameter vector from the scale defined by the model codes to another scale is specified as the \code{parameter.inv.transform} whilst the transformation mapping a parameter vector from the alternative scale to that on which the model is defined is specified as the \code{parameter.transform}. Modified: www/vignettes/pomp.pdf =================================================================== --- www/vignettes/pomp.pdf 2015-03-23 12:59:09 UTC (rev 1145) +++ www/vignettes/pomp.pdf 2015-03-23 12:59:14 UTC (rev 1146) @@ -1,54 +1,37 @@ %PDF-1.5 %???? 1 0 obj -<< /Type /ObjStm /Length 4535 /Filter /FlateDecode /N 99 /First 841 >> +<< /Type /ObjStm /Length 3934 /Filter /FlateDecode /N 99 /First 839 >> stream -x??\ks?6??~?m\)???J??ql+????[?[c??f3?Q??u???i??? G%?|o??%?$?h????ZU?  -S(? -[g -WH]? ?u,B!??E,? ??U!??Y???EU(??k??U?[([?B?B????P?????? -??)d,??x?[KD -?? -G?? ?"?Ma?[X?|AL? ? g??PxI???+????0?e?C???? ??"? -? -?H??"J????)h?>???b^???e??- &[????G??<]?h? -???$$%]?T??+??4t???< -(Cd??$??XPV4( P?????X?!P]XK -{??xv6[,??????ee???x9?????t1???{-w??tIJ/?'????}i.6???!??0?|??1?3?c>:?k??I?????z?/?+??d?????e?+??5??h?GS?hU?U?o??e?23?6>6?6????Ty???xDK&x??y?<-sw?25??9??6????j?X3???L?#3?????i?L?jT#0V ??@%KF? ?X???[f??h??????{?'x??2???????`:?-????????F????????#[?1|?|t|?|dz?\d???]??????a???5_?k?'?l?)?U2????????~?%X??94n?????!0?1???3?q,9?????? -?_i*~Ob??J?*S?-?=??7???????i#:?Mp? Q<*???????)????;[./?.?????O??i???|???xY??^??p6?A2??Q%??ztr??8G?\jG??+?7"tT8"?w??'??h?q??x9???rD*??[?/?|{z?F??Y??T?L?_!P???G???_A???b9_?M??x?#?E?FG^b???%&xzt?????)???J????3:??H?d?????x$?'???Q</?+q ^?Cq$??_?[?N??Gq,?g????G?D?"????1?}??'??8g?????z*????1?z??b*fb6???? ??????5Ot.??xv"??f?:?M?|w.bQ????X???????_3??????????w=??K H??}????????6?.fg??t.??????{??ty?5?a}??????v???6 -w??sc?W???d?d????2w&???K}s??"A?_???d???????LgM???? ?n?y>9????2$?y>??4_?s?????{????w????+?m??.???QHp? -^? -?@??2?2h?$^0p? ??e??W???ONj4?-4????Yo?R ?>mH?BQ(% -???fu?*?????P???????????? ???u??f,/J?7a/%?U?&?9??s?MR?c?Xk?w???5*vu`??7M?T?n?3????8w??M?l?L?y?????)i?`?ue?xI?(???c?vpSwj???c?h???)?cC?v?T??V<%?,????v????????O???Vx -?w???????ZxW oj?=-???w???????Y$??R6{??S?^?*?{?cO?Z?w?e???????Q?],?/u???R?#??!??]???,??)[??42 -???3hu?X??(c(???? ??bX]F????@??6q?\?>WN?2?WZ???ZoKo}?=??j??????r??\?1i????S?f^K? -? -???"S?f?m?aZli???"??? ?o?5?o=A??b???>lxX?X?zX?w???`?_???????w?1???x>???V?_9? -?r??ao?}?3jo????z{????(??'?#???J ?I(\c?E?7?7?}?]????.-?W?r????{-)?gH? ?>?hxB?.a 7??F?,???zW? ????R?Eo??[e^'??>b??+ ?#A? ?n`?N??j? -W0?*???*????????TTe??????)??O?xiI?7???t???????]?Kb/g????i%????%??? -???i???IU@??V?S???????"v?"}|*?J??C +%tiqQ ?????#d?;??uxH???P:y???(?zIS?"?w%V???Z?h? 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Bh???????????FU???]?????\v??'b{?}??P?vk????@?H???UwCPf P? *??T??J7??????"??S0Y1Wm8?n???M?- ?km?:?v???????M??<5\'s???f???t?FH?d?f?f*e]??h?Y?? +??7-?????X?F ?t??&?d?8??pr????k5??Rw???k ?2???q?q{?????????u}?w))?,???? +???????.pz+K?;_ ?nzR????? c??+ B?|????qt??P$Q?????(?MfW?H?[J?}??h.?u??5???????????T????C??SQ/????y{?#?e?[?????x?????g?????yzv?z??f???dvD?2 +FJ0??B7??P???B?N???(d??j&?????vrP??9' ??3HW???b??EW~?W??.?K +?B????mW1???dZ+?UJ{C??}?5*S??Os&? +??????|._?WrO????G?F??#?A??x>?????d$d%?8y('?????py$???o???LN??G9??j??'r&?r>???<%??V?uSZd9??b2????_??u???Rsw!?rY}??????e}??*Y?:?g???U~???????b~+'????i?G>???h?0?????o#s?w);$??on??L+Z?VN|1:?.u???h:??!o.???n????????7B!??xH???O<4A?? ?yt??6Z?????.?????p?ta????7sc?W?D?R????~?;???????:??y???V+wn???z?:kn????\n?}>;?R?{-4d?1sD???????q???m9?????????_u,????I?t?I|?? ?????I??|??????5??I???N?????@?j??????r:Z? ?:;.?r; ?E??????z????????:???e???5??2W?e^?[?l?k ?R?uX????m?Q???~9?.?U??????? ??,??[{??Z+v?5??Q]B????"???????HvY??v?kf??e???e???L;?f7[-K?????6???a`??b?x?|p????U?U??c?????Q????6!?B??w???9???]?=o??}T???wQ?&?v?W?????7P??)?>???x?????S?????=}?P??F???Rj?5???k???j??m?&&/??B?&L?;F???-S?B???v?-i#7???????&???????x?}?bM?0?kR+?/??99$?? +Jc??U??????t?????A? }????F?BY?l?\?EI?*4?9T&????k????*[x?%`????WA??6S??C?)l?^B?J??>k?R?jb?@Z,U?A?&??DE6?^?2A7?????hm??t??Y???gKW?"0?M????) +?/????n?u3?"??!*c?"?[???/&K?H_7EL???????????Z???????R?q???iP??B??(???at?? s}?"LaX?h?9N??a??h?1}>???Yf???>xP??( +!B?$? +Z???r?)o?????)?????i????JA?$?o???n??R?g)_w?)?????V???aZ???qE^?(}??K?R??A?;????~=?_??????ta4}????ReLu? +:???eQv?Y]?}?n.5ZV??r??9> @@ -57,12 +40,12 @@ - -2015-03-23T08:42:52-04:00 -2015-03-23T08:42:52-04:00 + +2015-03-23T08:58:17-04:00 +2015-03-23T08:58:17-04:00 Raph Levien - -Inconsolata + +Inconsolata @@ -70,500 +53,556 @@ endstream endobj 102 0 obj -<< /Type /ObjStm /Length 2433 /Filter /FlateDecode /N 99 /First 901 >> +<< /Type /ObjStm /Length 3149 /Filter /FlateDecode /N 99 /First 915 >> stream -x??[[o?~???/ - -g???A_??@?R?4-?@Sk? -E -$?????.I?A????!8;?????u?ec -)??aeS??+??kP????u?&???g???l??M??? 0?~?????y????Y???r.? *??IR.??6+3sF????(??G?l?????^?d0?.b??%E??????& -^?A??[??"%??1H29(?$?G???[Iq -29+o@?e??0?-?{??)dwf?????? w???\~?*,'??Y)| ?7??*x?? -!?R!y??????@8???e?G"\?Td???A???IX,???0?A??? X%[?x???: "? -?????D?????x-x????a ??X9??r ??Tv?X??;F???6&?I??e?KF? O ?D(??e l ]?~6?~X????\&?8??H?~M??`J???7?;Q?X?b?Vu?_????s%hn s1;?.?????????????J??{?|???~??|?????b???'???E??2N^?? o0????????"?/??_?x9?T?+?4????????,??????vR???? hAV???zY????? -qn??S?n}ho????K????????Dg???? ? ??? 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VY?Ht?H jW14??Z??a?2o?!b/?]??????G????? ??n?BA?(??Q?m????,`??)??h???endstream endobj 402 0 obj -<< /Type /ObjStm /Length 2739 /Filter /FlateDecode /N 99 /First 912 >> +<< /Type /ObjStm /Length 2728 /Filter /FlateDecode /N 99 /First 909 >> stream -x??[]o\I}?W?#?>0?A?AUH??y????I???')????C?B?VT???'\-x8?=J??P?? ????CI\TG? -p3????I??)?$?Z9?P???P?c%?T?` -U?8?,??I?z?.?V?Q&x(?I?=0F????,??\???M?C??J M?7??l???>??????????V%??\?H??B?y??^hz????4[Ka????h?0 -?oF???????pyF??Q 9????.)??!??c??S??:B/5????iG??"V?*?Y???? ]r. ??5reTt?? ?-?)x?,??????B?s?5??kXC??????g`?? ???,??6??j?7???6??*vXIi?%????T~??g???????7????)?????c????r???.'??;y ?????????????.?{????wp???$y??I??P??U?b?)????????????T[?lZ?AP?"5?`+?B??g??zH??Q R;?? ???l?0]?TOr.? -??!?h? -???rT??M>???m?x??*?5??RK?l{??tl?????P>??8K{\?[???????X???krAc?????d??8t?!?5?^"]f??c3????Llj ?)????'1}(?zq???C?%_}?Z?8K??,.??#?o???7 7< ?A[?E???6?????ki?[F$G$?R????m:?"???m:K?F?)??????3O/??>?SY????D????'?&?&???j????C1??c?0???(^[????????? -?JUC????.????JF?{???????~??S>M?e,?nB?E ??????CB????????c??m?<2?????b -?2?_g,???]7k??+J Author: kingaa Date: 2015-03-24 14:44:58 +0100 (Tue, 24 Mar 2015) New Revision: 1147 Modified: pkg/pomp/DESCRIPTION pkg/pomp/inst/CITATION Log: - update citation Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-23 12:59:14 UTC (rev 1146) +++ pkg/pomp/DESCRIPTION 2015-03-24 13:44:58 UTC (rev 1147) @@ -1,8 +1,8 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.63-3 -Date: 2015-03-23 +Version: 0.63-4 +Date: 2015-03-24 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), person(given=c("Edward","L."),family="Ionides",role=c("aut")), Modified: pkg/pomp/inst/CITATION =================================================================== --- pkg/pomp/inst/CITATION 2015-03-23 12:59:14 UTC (rev 1146) +++ pkg/pomp/inst/CITATION 2015-03-24 13:44:58 UTC (rev 1147) @@ -1,3 +1,6 @@ +year <- sub("-.*", "", meta$Date) +note <- sprintf("R package version %s", meta$Version) + citHeader("To cite the pomp package in publications use:") citEntry( @@ -2,3 +5,3 @@ entry="Manual", - title="pomp: Statistical inference for partially observed Markov processes (R package)", + title="{pomp}: {S}tatistical Inference for Partially Observed {M}arkov Processes", author=personList( @@ -16,13 +19,12 @@ as.person("Helen Wearing"), as.person("Simon N. Wood") ), - year=2014, - url="http://pomp.r-forge.r-rproject.org", - textVersion=paste( - "A. A. King, E. L. Ionides, C. M. Bret\\'o, S. P. Ellner, M. J. Ferrari, B. E. Kendall, M. Lavine, D. Nguyen, D. C. Reuman, H. Wearing, and S. N. Wood", - "pomp: Statistical inference for partially observed Markov processes (R package)", - "http://pomp.r-forge.r-project.org" - ) - ) - -citFooter("As pomp is continually evolving, you may want to cite its version number. Find it with 'help(package=pomp)'.") + year=year, + note=note, + url=meta$URL, + textVersion=paste0( + "A. A. King, E. L. Ionides, C. M. Breto, S. P. Ellner, M. J. Ferrari, B. E. Kendall, M. Lavine, D. Nguyen, D. C. Reuman, H. Wearing, and S. N. Wood"," (",year,") ", + "pomp: Statistical Inference for Partially Observed Markov Processes (R package). ", + meta$URL + ) + ) From noreply at r-forge.r-project.org Tue Mar 24 15:19:19 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Tue, 24 Mar 2015 15:19:19 +0100 (CET) Subject: [Pomp-commits] r1148 - www/vignettes Message-ID: <20150324141919.76FF8186E77@r-forge.r-project.org> Author: kingaa Date: 2015-03-24 15:19:18 +0100 (Tue, 24 Mar 2015) New Revision: 1148 Modified: www/vignettes/pomp.pdf www/vignettes/pompjss.R www/vignettes/pompjss.Rnw www/vignettes/pompjss.bib www/vignettes/pompjss.pdf Log: - update vignette Modified: www/vignettes/pomp.pdf =================================================================== --- www/vignettes/pomp.pdf 2015-03-24 13:44:58 UTC (rev 1147) +++ www/vignettes/pomp.pdf 2015-03-24 14:19:18 UTC (rev 1148) @@ -10,7 +10,8 @@ ???@ -? ????? !?W?O ?p????,??????????1???7G?6SsU??Q|???9X?? _v|?|??=a|Mc|??l??6???Pt?(??m???e?\??? k!y?? ?^??E?????c????Fj?>??\??g?9?zH|??Zs?Z3??pM?????&????G?]?\_??M?6????5X-c????>9V?7?x?1?y?"k?}?????????5Y?a?lU?????-?????????????c?#?c?&??s,?U??s,??<6??X?cy???%???????[g x?|8Y,???g#??i:?U?WK?\?????jA??, &???tJ?_P????? S+????????h?Xnm?N;8?)???O[l ????g??X? Bh???????????FU???]?????\v??'b{?}??P?vk????@?H???UwCPf P? *??T??J7??????"??S0Y1Wm8?n???M?- ?km?:?v???????M??<5\'s???f???t?FH?d?f?f*e]??h?Y?? @@ -31,7 +32,7 @@ :???eQv?Y]?}?n.5ZV??r??9?eQv?Y]?}?n.5ZV??r??9> @@ -40,12 +41,12 @@ - -2015-03-23T08:58:17-04:00 -2015-03-23T08:58:17-04:00 + +2015-03-24T10:07:19-04:00 +2015-03-24T10:07:19-04:00 Raph Levien - -Inconsolata + +Inconsolata @@ -587,20 +588,19 @@ ??B,??4?,:?/????`??{?@???j?7?!??+?n?x???W?Qendstream endobj 1014 0 obj -<< /Filter /FlateDecode /Length 1357 >> +<< /Filter /FlateDecode /Length 1358 >> stream -x??W???6????[?"????*??iSi4??}?(%?^%???r???wH????-??Kr8?3g?OA?I????j77?y??& -N?ObO???j???" h???????qWI@???i?0ey?o7???-?p?W?IlC??u???e???s??q?Bp???8?cSV!?qNr?;???\U?p?)pQ?????3?hDR?* ? ????,?,M??0???9W?m??=B??s -?=?b)@Y??H (?|k???????P9"Q???Y?????>??????7c?,C???P??<|$EG??b??j?4????R ??D???/7h~t?Is$? ? }?~?d%?z?Z??+6w???-L?)CB?Zvk??9&??E@?8???O?{?%??%?h?AVd???p!???????!%?s??????i?y???MRXR?/??n???8-?$-p?17???ssc??U? -?i???? 6?Q??Q -,l.?????Q??$ ???4!&>z)t??~0 -y?]?`j2????V ????&???????l???G?~"?H??????-? ?{n&??}????uh i1??S? -???(???A??????+P*?=??M???h????E??? ?E=?7!8% ?????????Rc??n?? h??^??}?3????^?a-t\`Z?>?)TO?(:)??????P?y??j't?A?? -t45C?lQ%???1??e?V4A??????Vk??BqWW??kb?h"??ov C?n?e??P)??_ at G?Z?2?0? hPg?? ??J?^??????{]?g??|w.?`?????A??7r???g???Uh&?<%)???Y1?~M??2 -?w??n??H??????????`^??K?2(?*@s????F"??3[M??}??jyg=??Q?\??F?u?G?4??@???d???9?????3???v @9?N(`???:'??P????d VT@???>CW??????0GH\???n?C}s>???v*??`L2t???P??H!K??? ???a? ?:5?? -? ??,G??8? -?Mx?>uK7J>k??9H?,e3g?R??]???:S????S_?p??? 5~?S??????5?????z?Y???>Aj|???????x211?=?^a??^M??Y"0{????x?yNj???&???/P???E??u??f0????????H?^?????????6??#?M???j? ??" Q???????M?R?r0~? ??|?i?F1d??w? +)???+?????O??? +?h???Zyx?p;??)??<`I?Y????}?????;??6??A?N?-?$C?Vd?c8p??\?}W?G?Y0Fq????^JS???mC?b?0Lm??V????^?g?D??1??Z? +?????MdH??;??????Uy/?d?c????M:?B????????9?sd.???y>???(?N???&j?A??n??D?<?? ?d =???FFxo??w???c??n; +?`{-??k????~?tJ?k???<#?B?????}U?[5??V?fB?;UCG+?0???? ?/s.:P6gEz?????z?Z????????Yp??GI~?[??9?w??(???J????:"???b??Y@?>?5????????=?@???sf??w??f1??)??L+?h[u?i?^?v??S?9????????+???.??f??2?wR???gu?P???eP???o?fnu??@??~??0M9???5]? ?6??T??2??G???b7r?SF? ??4??/V??G;> @@ -906,21 +906,25 @@ stream x??Z?s?6??????-??@`w??&{???n[??!?M?[?TI*???} ????Jr?H????>??"??"???o????g?.???xq???????Sn?^C??E????wW8tG?????=?t?-??Q?????J???n?+????jy?+?c????46????P??gA?Ug???b? ???????m1??J????h??q??F????wO9????????b+?G*5,?zS? ???/?a?'???a?v????[?O????Psk"?X,?f????(U6?N??????w????t?`uRtm??2MA3??a?y ??1?,g??v=wX3l?:\Bw?kU??_???????>?;??~~?o?R????9?M??m????x??Ne? ?"?,%,;OE???aW???#??R\5C?o????a -??????+?)??+?a????=?P????}??????&???=?%??v??7n ?&10E??9? 3?P??<?<D?????????0????? -UE??LFU?9?`??e?? ??~??+9\?kv??y?CL?% -E????6??T??(?4=?l.??u???j?PQ?(???I#u?^??????&yIav????V?b,7??4~???%?I??N|???????H?p?????xP -8d???&??x)???????4?o???~[?3,g=??h2c??Lfl?gO?e??.?g???8?iC???.?M??R??}M??B???b???K??2???L??{??+?p!\3?p%?ira?M????"???P??*?A?O?3?7?zF???n?p??:?FG?)???7?d?'95?9???W??&???1??fq???J-b?U????X??]??'?3?G?W6??????t?c??i??1?????)?`?m?yx???n?v?? ?^EY7?+J?6???u?E????SM?L?*???K;yp???)9'?K?R??????w??Z??>l???0m?x?^ I?????G?_??`?M??pu????N`y???+??Z ??M=?0???oh?mp?2c?H????Q??M?_?S??vo??$?? ?y?~?wVHr?R?xI???BTN?~?????A/?????-kb????85????.????*RS`UxE?*%????C1}pvD???#??-:?Z?w?f?????jvs2q?w??8????C]?^??l?Z????0Rs?/?@?????Y???g vu??r?V' -?I"p??-r??_?????????u??x?>???$???0????R_??(:?Ap0?'A@???????0???K?? s?????w;%??8Iy!?QR?@???/?/O"?c?!s??=e2?]?6?K?endstream +??????+?)??+?a????=?P????}??????&???=?%??v??7n ?&10E??9?lg?2???RWr????(' ??????K?B +?q?m.??T?Q iz??\x??{??MO??????}??v???????P?? @?F?`?b?-???L?,????}w[???Xn??i??A?K???????sq??????y?-??p??s Mj??R??}1a?i(??????hgX?"z`A?d??s??????????] ?LG?q???>?c < +\ %???????z????7?????ejw?????H?W?B?6f??J0??"?????T?}?Y}e#?g.???????S?6??v???9?;??(??a???Nw6A??~?C???m?????P?S8????=?9?MgW3?x$?>????Y????? ??AGG???????] ?????4b0?&^?8??D???_?Q???*???b?p??9C&g9&?M????]?N?&????g?Q????~???????3?8g?.T??D?3?x?/?-@NQ(?d?[?a4?]?o?-.p?@qK?D ep.A<.J? +???%???b??KR:?3??A???p??Ow_?y????o???n??4mVQ???L?j??U??@??*??L]?a?r^j??W???4v?zy??^???S???K`I????51????i v?]???????a7?i??K]g?,?3:](M7 +???q?}???h??~WC?>?}ElJ???4???3?[????0.?n;*??jb?\J??R??"??????U???d?????????|??UG???2}d#!?za. +?7?????Ze?~???mE +????????7???0?I?!??\/???????&??9??$0S???,???-?T?O| +r???k??4W??oo+$????Mmz??G\??2(?? T???#??&N?o1t?2??*??w?c_??=?y?W3?,???F?? +I0=??e??+L?F_??$???????JOI??P?Y?f??M,??`??)n???~R~? +?q?|&x/?????k??_.?u????}K??Z?$J??o?????;?r?%q?0?Ad????????$9?n??@?c&> @@ -2603,14 +2607,11 @@ %??{?P???endstream endobj 1091 0 obj -<< /Type /XRef /Length 435 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 1092 /ID [<213d0053ec1e0a53c3006db272349d0d>] >> +<< /Type /XRef /Length 436 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 1092 /ID [<1654c5e3a24271b3b3682c1ec6893f4a><0c9132f9484649268e66406e7f421aef>] >> stream -x???=(Eq??}/?z_???P)e %?????z? H?G!???b?0 ?2I)? ??[?F??????x???t???s????>?%??mY.|??J?F6R?V?q???:X#?/;?? }C???i?Fa??6*??D?o????.x??dBh7 -???4f? -??=_?n)??8?t;??Sj??'0" ~/?Sf??3????}X?U?JPF??)a;???3s??d?????+aF?]T?? ???5S?????n??????69e?p?0? -]?I?'z?FB-??????=???-???x;?J??f?P/???<y??I?W#?]y?N??$?d? +x???M(DQ???? Author: kingaa Date: 2015-03-24 17:24:30 +0100 (Tue, 24 Mar 2015) New Revision: 1149 Modified: pkg/pomp/inst/CITATION Log: - improve citation Modified: pkg/pomp/inst/CITATION =================================================================== --- pkg/pomp/inst/CITATION 2015-03-24 14:19:18 UTC (rev 1148) +++ pkg/pomp/inst/CITATION 2015-03-24 16:24:30 UTC (rev 1149) @@ -1,5 +1,5 @@ year <- sub("-.*", "", meta$Date) -note <- sprintf("R package version %s", meta$Version) +note <- sprintf("R package, version %s", meta$Version) citHeader("To cite the pomp package in publications use:") @@ -24,7 +24,7 @@ url=meta$URL, textVersion=paste0( "A. A. King, E. L. Ionides, C. M. Breto, S. P. Ellner, M. J. Ferrari, B. E. Kendall, M. Lavine, D. Nguyen, D. C. Reuman, H. Wearing, and S. N. Wood"," (",year,") ", - "pomp: Statistical Inference for Partially Observed Markov Processes (R package). ", - meta$URL + "pomp: Statistical Inference for Partially Observed Markov Processes ", + note,". ",meta$URL ) ) From noreply at r-forge.r-project.org Tue Mar 24 20:32:51 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Tue, 24 Mar 2015 20:32:51 +0100 (CET) Subject: [Pomp-commits] r1150 - www/vignettes Message-ID: <20150324193251.B2AD11877E8@r-forge.r-project.org> Author: kingaa Date: 2015-03-24 20:32:50 +0100 (Tue, 24 Mar 2015) New Revision: 1150 Modified: www/vignettes/pomp.pdf www/vignettes/pompjss.R www/vignettes/pompjss.Rnw www/vignettes/pompjss.bib www/vignettes/pompjss.pdf Log: - small fixes Modified: www/vignettes/pomp.pdf =================================================================== --- www/vignettes/pomp.pdf 2015-03-24 16:24:30 UTC (rev 1149) +++ www/vignettes/pomp.pdf 2015-03-24 19:32:50 UTC (rev 1150) @@ -11,7 +11,7 @@ -? ????? !?W?O ?p????,??????????1???7G?6SsU??Q|???9X?? _v|?|??=a|Mc|??l??6???Pt?(??m???e?\??? k!y?? ?^??E?????c????Fj?>??\??g?9?zH|??Zs?Z3??pM?????&????G?]?\_??M?6????5X-c????>9V?7?x?1?y?"k?}?????????5Y?a?lU?????-?????????????c?#?c?&??s,?U??s,??<6??X?cy???%???????[g x?|8Y,???g#??i:?U?WK?\?????jA??, &???tJ?_P????? S+????????h?Xnm?N;8?)???O[l ????g??X? Bh???????????FU???]?????\v??'b{?}??P?vk????@?H???UwCPf P? *??T??J7??????"??S0Y1Wm8?n???M?- ?km?:?v???????M??<5\'s???f???t?FH?d?f?f*e]??h?Y?? @@ -32,7 +32,7 @@ :???eQv?Y]?}?n.5ZV??r??9?eQv?Y]?}?n.5ZV??r??9> @@ -41,12 +41,12 @@ - -2015-03-24T10:07:19-04:00 -2015-03-24T10:07:19-04:00 + +2015-03-24T15:20:55-04:00 +2015-03-24T15:20:55-04:00 Raph Levien - -Inconsolata + +Inconsolata @@ -2607,7 +2607,7 @@ %??{?P???endstream endobj 1091 0 obj -<< /Type /XRef /Length 436 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 1092 /ID [<1654c5e3a24271b3b3682c1ec6893f4a><0c9132f9484649268e66406e7f421aef>] >> +<< /Type /XRef /Length 436 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Info 3 0 R /Root 2 0 R /Size 1092 /ID [<25a48ba635e277ad025f5ef26ba3c7f2><6bf50825d4ac84ee13149a7cf8900a7e>] >> stream x???M(DQ????="0.62-5") +stopifnot(packageVersion("pomp")>="0.63-4") ## ----set-opts,include=F,cache=F------------------------------------------ @@ -58,6 +58,7 @@ ## ----set-seed,cache=F,include=F------------------------------------------ set.seed(5384959L) +options(cores=10) ## ----bake,include=FALSE,cache=FALSE-------------------------------------- @@ -271,7 +272,7 @@ require(doMC) require(foreach) - registerDoMC(10) + registerDoMC() save.seed <- .Random.seed set.seed(334388458L,kind="L'Ecuyer") @@ -399,7 +400,7 @@ tic <- Sys.time() require(doMC) require(foreach) - registerDoMC(5) + registerDoMC() save.seed <- .Random.seed set.seed(334388458L,kind="L'Ecuyer") @@ -427,11 +428,11 @@ rm(pmcmc1,save.seed,tic,toc) }) -## ----pmcmc-diagnostics,results="hide",fig.show="hide",echo=F,eval=F------ -## gelman.diag(pmcmc.traces) -## gelman.plot(pmcmc.traces) -## autocorr.plot(pmcmc.traces[[1]]) -## hist(rle(unlist(pmcmc.traces[,"r"]))$length) +## ----pmcmc-diagnostics,results="hide",fig.show="hide",echo=F,eval=T------ +gelman.diag(pmcmc.traces) +gelman.plot(pmcmc.traces) +autocorr.plot(pmcmc.traces[[1]]) +hist(rle(unlist(pmcmc.traces[,"r"]))$length) ## ----pmcmc-plot,echo=F,eval=T,results="hide",cache=TRUE------------------ op <- par(mar=c(4,3.5,0,1),mfcol=c(3,2),mgp=c(2.5,1,0),cex.axis=1.5,cex.lab=2) @@ -568,7 +569,7 @@ require(magrittr) require(foreach) require(doMC) - registerDoMC(10) + registerDoMC() rbind(guess=guess, truth=coef(ricker), @@ -644,7 +645,7 @@ tic <- Sys.time() require(doMC) require(foreach) - registerDoMC(5) + registerDoMC() save.seed <- .Random.seed set.seed(334388458L,kind="L'Ecuyer") @@ -668,11 +669,11 @@ abc.traces <- conv.rec(abc1,c("r","sigma","tau")) abc.traces <- window(abc.traces,start=2000001,thin=400) ess.abc <- effectiveSize(abc.traces) -rm(abc1,save.seed,tic,toc) +rm(abc1,save.seed,tic,toc) }) -## ----abc-diagnostics,results="hide",fig.show="hide",echo=F--------------- +## ----abc-diagnostics,results="hide",fig.show="hide",echo=FALSE,eval=TRUE---- gelman.diag(abc.traces) gelman.plot(abc.traces) autocorr.plot(abc.traces[[1]]) @@ -728,7 +729,7 @@ bake("nlf-mif-compare.rda",{ require(doMC) require(foreach) - registerDoMC(10) + registerDoMC() save.seed <- .Random.seed set.seed(816326853L,kind="L'Ecuyer") Modified: www/vignettes/pompjss.Rnw =================================================================== --- www/vignettes/pompjss.Rnw 2015-03-24 16:24:30 UTC (rev 1149) +++ www/vignettes/pompjss.Rnw 2015-03-24 19:32:50 UTC (rev 1150) @@ -122,9 +122,6 @@ %% Telephone: +43/512/507-7103 %% Fax: +43/512/507-2851 -%% for those who use Sweave please include the following line (with % symbols): -%% need no \usepackage{Sweave.sty} -%% publication information %% NOTE: Typically, this can be left commented and will be filled out by the technical editor %% \Volume{50} %% \Issue{9} @@ -148,7 +145,7 @@ require(reshape2) require(xtable) -stopifnot(packageVersion("pomp")>="0.62-5") +stopifnot(packageVersion("pomp")>="0.63-4") <>= options( @@ -193,6 +190,7 @@ <>= set.seed(5384959L) +options(cores=10) <>= bake <- function (file, expr) { @@ -231,7 +229,7 @@ In particular, when linear, Gaussian approximations are adequate for one's purposes, or when the latent process takes values in a small, discrete set, methods that exploit these additional assumptions to advantage, such as the extended and ensemble Kalman filter methods or exact hidden-Markov-model methods, are available, but not yet as part of \pkg{pomp}. It is the class of nonlinear, non-Gaussian POMP models with large state spaces upon which \pkg{pomp} is focused. -A POMP model may be characterized by the transition density for the Markov process and the measurement density\footnote{We use the term ``density'' in this article encompass both the continuous and discrete cases. +A POMP model may be characterized by the transition density for the Markov process and the measurement density\footnote{We use the term ``density'' in this article encompass both the continuous and discrete cases. Thus, in the latter case, i.e., when state variables and/or measured quantities are discrete, one could replace ``probability density function'' with ``probability mass function''.}. However, some methods require only simulation from the transition density whereas others require evaluation of this density. Still other methods may not work with the model itself but with an approximation, such as a linearization. @@ -547,7 +545,7 @@ In \cref{alg:pfilter:systematic} of \cref{alg:pfilter}, systematic resampling (\cref{alg:systematic}) is used in preference to multinomial resampling. \Cref{alg:systematic} reduces Monte~Carlo variability while resampling with the proper marginal probability. In particular, if all the particle weights are equal then \cref{alg:systematic} has the appropriate behavior of leaving the particles unchanged. -As pointed out by \citep{douc05}, stratified resampling performs better than multinomial sampling and \cref{alg:systematic} is in practice comparable in performance to stratified resampling and somewhat faster. +As pointed out by \citep{douc05}, stratified resampling performs better than multinomial sampling and \cref{alg:systematic} is in practice comparable in performance to stratified resampling and somewhat faster. \pagebreak @@ -623,7 +621,7 @@ \item It preserves the plug-and-play property, inherited from the particle filter. \end{enumerate} Iterated filtering is implemented in the \code{mif} function. -By default, \code{mif} carries out the procedure of \citet{ionides06}. +By default, \code{mif} carries out the procedure of \citet{ionides06}. The improved iterated filtering algorithm (IF2) of \citet{ionides15} has shown promise. A limited version of IF2 is available via the \code{method="mif2"} option; a full version of this algorithm will be released soon. @@ -1210,7 +1208,7 @@ require(doMC) require(foreach) - registerDoMC(10) + registerDoMC() save.seed <- .Random.seed set.seed(334388458L,kind="L'Ecuyer") @@ -1315,7 +1313,7 @@ The first three columns show the estimated values of the three parameters. The next two columns show the log likelihood, $\loglikMC$, estimated by SMC (\cref{alg:pfilter}) and its standard error, respectively. The exact log likelihood, $\ell$, is shown in the rightmost column. - An ideal likelihood-ratio $95\%$ confidence set, not usually computationally available, includes all parameters having likelihood within \code{qchisq(0.95,df=3)/2 = 3.91} of the exact MLE. + An ideal likelihood-ratio $95\%$ confidence set, not usually computationally available, includes all parameters having likelihood within \code{qchisq(0.95,df=3)/2 = 3.91} of the exact MLE. We see that both the \code{mif} MLE and the truth are in this set. In this example, the \code{mif} MLE is close to the exact MLE, so it is reasonable to expect that profile likelihood confidence intervals and likelihood ratio tests constructed using the \code{mif} MLE have statistical properties similar to those based on the exact MLE. \label{tab:gompertz-multi-mif-table} @@ -1366,7 +1364,7 @@ tic <- Sys.time() require(doMC) require(foreach) - registerDoMC(5) + registerDoMC() save.seed <- .Random.seed set.seed(334388458L,kind="L'Ecuyer") @@ -1391,7 +1389,7 @@ ess.pmcmc <- effectiveSize(pmcmc.traces) rm(pmcmc1,save.seed,tic,toc) }) -<>= +<>= gelman.diag(pmcmc.traces) gelman.plot(pmcmc.traces) autocorr.plot(pmcmc.traces[[1]]) @@ -1624,7 +1622,7 @@ require(magrittr) require(foreach) require(doMC) - registerDoMC(10) + registerDoMC() rbind(guess=guess, truth=coef(ricker), @@ -1711,7 +1709,7 @@ tic <- Sys.time() require(doMC) require(foreach) - registerDoMC(5) + registerDoMC() save.seed <- .Random.seed set.seed(334388458L,kind="L'Ecuyer") @@ -1733,10 +1731,10 @@ abc.traces <- conv.rec(abc1,c("r","sigma","tau")) abc.traces <- window(abc.traces,start=2000001,thin=400) ess.abc <- effectiveSize(abc.traces) -rm(abc1,save.seed,tic,toc) +rm(abc1,save.seed,tic,toc) }) -<>= +<>= gelman.diag(abc.traces) gelman.plot(abc.traces) autocorr.plot(abc.traces[[1]]) @@ -1832,7 +1830,7 @@ bake("nlf-mif-compare.rda",{ require(doMC) require(foreach) - registerDoMC(10) + registerDoMC() save.seed <- .Random.seed set.seed(816326853L,kind="L'Ecuyer") @@ -2037,12 +2035,12 @@ \prob{\dlta{\cp{R}{\BirthDeath}(t)}\myequals 1 \given S(t), I(t), R(t)} &= \mu\,R(t)\,h+o(h), \end{aligned} \end{equation} -together with statement that all events of the form +together with statement that all events of the form \begin{equation*} - \{\dlta{\cp{A}{B}(t)}\,{>}\, 1\} \qquad \text{and} \qquad \{\dlta{\cp{A}{B}(t)}\myequals 1,\dlta{\cp{C}{D}(t)}\myequals 1\} + \{\dlta{\cp{A}{B}(t)}\,{>}\, 1\} \qquad \text{and} \qquad \{\dlta{\cp{A}{B}(t)}\myequals 1,\dlta{\cp{C}{D}(t)}\myequals 1\} \end{equation*} for $A$, $B$, $C$, $D$ with $(A,B)\neq (C,D)$ have probability $o(h)$. -The counting processes are coupled to the state variables \citep{breto11} via the following identities +The counting processes are coupled to the state variables \citep{breto11} via the following identities \begin{equation}\label{eq:sir-cp-bal} \begin{aligned} \dlta{S}(t) &= \dlta{\cp{\BirthDeath}{S}}(t)-\dlta{\cp{S}{I}}(t)-\dlta{\cp{S}{\BirthDeath}}(t),\\ Modified: www/vignettes/pompjss.bib =================================================================== --- www/vignettes/pompjss.bib 2015-03-24 16:24:30 UTC (rev 1149) +++ www/vignettes/pompjss.bib 2015-03-24 19:32:50 UTC (rev 1150) @@ -56,7 +56,7 @@ } @Article{andrieu10, - Title = {Particle {M}arkov Chain {M}onte {C}arlo}, + Title = {Particle {M}arkov Chain {M}onte {C}arlo Methods}, Author = {Andrieu, Christophe and Doucet, Arnaud and Holenstein, Roman}, Journal = JRSSB, Year = {2010}, Modified: www/vignettes/pompjss.pdf =================================================================== --- www/vignettes/pompjss.pdf 2015-03-24 16:24:30 UTC (rev 1149) +++ www/vignettes/pompjss.pdf 2015-03-24 19:32:50 UTC (rev 1150) @@ -3210,260 +3210,278 @@ /Height 900 /BitsPerComponent 8 /ColorSpace /DeviceGray -/Length 47112 +/Length 46531 /Filter /FlateDecode >> stream -x?????D?s?JT,(6????bE?D???"?????Q?`??{E??????"E?J?w????d????l9.????\2If??????[4?B!?B!?B!?B!?B!?B!?B!?B!?B!?B!?B!?B!?B!?B!?B!?B!?B!?B!?B????4fKBH?0:{?%!??N!??N!??N!??N!??N!?????k?N??X??????: ?{??9_8??????k?R?A??W??7?o????? 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N?????? ?S????fUu??]F?]Q~?1Xo??4??y?W?6??Z?Xx$??4?P?+wc??bkZ??&?L??Y?g?!W???)?????????i???????G??,?[?-?{?CJ??GL?OrublP??F?e??7?0???-BS?????..? +?]^?QE?sD_?0?]??KoIm?:??C??r?_??s/?j{???C??G?fe?G?{M?a{???D?"\??????0???GO?:??x?\P?{?I????O???H??#??n?MM??4i,xo"??t^*??Kus??????????????????=m?????S??? [TRUNCATED] To get the complete diff run: svnlook diff /svnroot/pomp -r 1150 From noreply at r-forge.r-project.org Wed Mar 25 14:26:33 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Wed, 25 Mar 2015 14:26:33 +0100 (CET) Subject: [Pomp-commits] r1151 - in pkg/pomp: . inst Message-ID: <20150325132633.2A133186997@r-forge.r-project.org> Author: kingaa Date: 2015-03-25 14:26:32 +0100 (Wed, 25 Mar 2015) New Revision: 1151 Modified: pkg/pomp/DESCRIPTION pkg/pomp/inst/CITATION Log: - update citation Modified: pkg/pomp/DESCRIPTION =================================================================== --- pkg/pomp/DESCRIPTION 2015-03-24 19:32:50 UTC (rev 1150) +++ pkg/pomp/DESCRIPTION 2015-03-25 13:26:32 UTC (rev 1151) @@ -1,8 +1,8 @@ Package: pomp Type: Package Title: Statistical Inference for Partially Observed Markov Processes -Version: 0.63-4 -Date: 2015-03-24 +Version: 0.63-5 +Date: 2015-03-25 Authors at R: c(person(given=c("Aaron","A."),family="King", role=c("aut","cre"),email="kingaa at umich.edu"), person(given=c("Edward","L."),family="Ionides",role=c("aut")), Modified: pkg/pomp/inst/CITATION =================================================================== --- pkg/pomp/inst/CITATION 2015-03-24 19:32:50 UTC (rev 1150) +++ pkg/pomp/inst/CITATION 2015-03-25 13:26:32 UTC (rev 1151) @@ -1,9 +1,33 @@ year <- sub("-.*", "", meta$Date) -note <- sprintf("R package, version %s", meta$Version) +note1 <- sprintf("R~package, version~%s", meta$Version) +note2 <- sprintf("(R package, version %s)", meta$Version) -citHeader("To cite the pomp package in publications use:") +citEntry( + header=paste("To cite the",sQuote("pomp"), + "package in publications, please use:"), + entry="Article", + title="Statistical Inference for Partially Observed {M}arkov Processes via the {R} Package {pomp}", + author=personList( + as.person("Aaron A. King"), + as.person("Dao Nguyen"), + as.person("Edward L. Ionides") + ), + year=2015, + journal="Journal of Statistical Software", + volume="in press", +# number=XX, +# url="http://www.jstatsoft.org/vXX/iXX", + textVersion=paste0( + "Aaron A. King, Dao Nguyen, Edward L. Ionides", + " (2015) ", + "Statistical Inference for Partially Observed Markov Processes via the R Package pomp. ", + "Journal of Statistical Software, in press. " +# "http://www.jstatsoft.org/vXX/iXX" + ) + ) citEntry( + header="The correct citation of the package itself is:", entry="Manual", title="{pomp}: {S}tatistical Inference for Partially Observed {M}arkov Processes", author=personList( @@ -20,11 +44,14 @@ as.person("Simon N. Wood") ), year=year, - note=note, + note=note1, url=meta$URL, textVersion=paste0( "A. A. King, E. L. Ionides, C. M. Breto, S. P. Ellner, M. J. Ferrari, B. E. Kendall, M. Lavine, D. Nguyen, D. C. Reuman, H. Wearing, and S. N. Wood"," (",year,") ", "pomp: Statistical Inference for Partially Observed Markov Processes ", - note,". ",meta$URL + note2,". ",meta$URL ) ) + +citFooter("To obtain these citations in BibTeX format, do ", + sQuote("toBibtex(citation(\"pomp\"))"))
    Statistical Inference for Partially Observed Markov Processes via the R Package pomp(PDF)(R code)
    Getting started with pomp (HTML) (R code)(HTML) (R code)
    An example using IF2(HTML)(R code)
    pomp package manual (PDF)