[Pomp-commits] r138 - pkg/man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Tue Jun 2 21:20:27 CEST 2009


Author: kingaa
Date: 2009-06-02 21:20:25 +0200 (Tue, 02 Jun 2009)
New Revision: 138

Modified:
   pkg/man/bsplines.Rd
   pkg/man/dmeasure-pomp.Rd
   pkg/man/dprocess-pomp.Rd
   pkg/man/euler.Rd
   pkg/man/euler.sir.Rd
   pkg/man/eulermultinom.Rd
   pkg/man/init.state-pomp.Rd
   pkg/man/mif-class.Rd
   pkg/man/mif-methods.Rd
   pkg/man/mif.Rd
   pkg/man/nlf.Rd
   pkg/man/ou2.Rd
   pkg/man/particles-mif.Rd
   pkg/man/pfilter.Rd
   pkg/man/pomp-class.Rd
   pkg/man/pomp-methods.Rd
   pkg/man/pomp-package.Rd
   pkg/man/pomp.Rd
   pkg/man/rmeasure-pomp.Rd
   pkg/man/rprocess-pomp.Rd
   pkg/man/simulate-pomp.Rd
   pkg/man/skeleton-pomp.Rd
   pkg/man/sobol.Rd
   pkg/man/trajectory-pomp.Rd
Log:
further improvements to documentation

Modified: pkg/man/bsplines.Rd
===================================================================
--- pkg/man/bsplines.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/bsplines.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -4,7 +4,7 @@
 \title{B-spline bases}
 \description{
   These functions generate B-spline basis functions.
-  \code{bspline.basis} gives a set of basis functions.
+  \code{bspline.basis} gives a basis of spline functions.
   \code{periodic.bspline.basis} gives a basis of periodic spline functions.
 }
 \usage{
@@ -27,7 +27,7 @@
     The basis functions returned are periodic with period \code{period}.
   }
 }
-\author{Aaron A. King (kingaa at umich dot edu)}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
 \examples{
 x <- seq(0,2,by=0.01)
 y <- bspline.basis(x,degree=3,nbasis=9)

Modified: pkg/man/dmeasure-pomp.Rd
===================================================================
--- pkg/man/dmeasure-pomp.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/dmeasure-pomp.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -5,7 +5,9 @@
 \alias{dmeasure-pomp}
 \title{Evaluate the probability density of observations given underlying states in a partially-observed Markov process}
 \description{
-  The method \code{dmeaure} evaluates the probability density of a set of measurements given the state of the system.
+  The method \code{dmeasure} evaluates the probability density of a set of measurements given the state of the system.
+  This function is part of the low-level interface to \code{pomp} objects.
+  This help page does not give instructions on the implementation of models: see \code{\link{pomp}} for instructions.
 }
 \usage{
 dmeasure(object, y, x, times, params, log = FALSE, \dots)
@@ -20,7 +22,6 @@
   \item{x}{
     a rank-3 array containing the states of the unobserved process.
     The dimensions of \code{x} are \code{nvars} x \code{nreps} x \code{ntimes}, where \code{nvars} is the number of state variables, \code{nreps} is the number of replicates, and \code{ntimes} is the length of \code{times}.
-    Note that if \code{ntimes != length(times)} or \code{ntimes != ncol(y)}, an error is generated.
   }
   \item{times}{
     a numeric vector containing the times at which the observations were made.
@@ -29,7 +30,7 @@
     a rank-2 array of parameters with columns corresponding to the columns of \code{x}.
     Note that the \code{x} and \code{params} must agree in the number of their columns.
   }
-  \item{log}{if TRUE, probabilities p are given as log(p).}
+  \item{log}{if TRUE, log probabilities are returned.}
   \item{\dots}{at present, these are ignored.}
 }
 \value{
@@ -40,8 +41,7 @@
   This function is essentially a wrapper around the user-supplied \code{dmeasure} slot of the \code{pomp} object.
   For specifications on writing such a function, see \code{\link{pomp}}.
 }
-\references{}
-\author{Aaron A. King (kingaa at umich dot edu)}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
 \seealso{\code{\link{pomp-class}}, \code{\link{pomp}}}
 \keyword{models}
 \keyword{ts}

Modified: pkg/man/dprocess-pomp.Rd
===================================================================
--- pkg/man/dprocess-pomp.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/dprocess-pomp.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -8,6 +8,8 @@
 }
 \description{
   The method \code{dprocess} evaluates the probability density of a set of consecutive state transitions.
+  This function is part of the low-level interface to \code{pomp} objects.
+  This help page does not give instructions on the implementation of models: see \code{\link{pomp}} for instructions.
 }
 \usage{
 dprocess(object, x, times, params, log = FALSE, \dots)
@@ -18,7 +20,6 @@
   \item{x}{
     a rank-3 array containing the states of the unobserved process.
     The dimensions of \code{x} are \code{nvars} x \code{nreps} x \code{ntimes}, where \code{nvars} is the number of state variables, \code{nreps} is the number of replicates, and \code{ntimes} is the length of \code{times}.
-    Note that if \code{nreps != nrow(y)} or \code{ntimes-1 != length(times)}, an error is generated.
   }
   \item{times}{
     a numeric vector containing the times corresponding to the given states.
@@ -27,7 +28,7 @@
     a rank-2 array of parameters with columns corresponding to the columns of \code{x}.
     Note that the \code{x} and \code{params} must agree in the number of their columns.
   }
-  \item{log}{if TRUE, probabilities p are given as log(p).}
+  \item{log}{if TRUE, log probabilities are returned.}
   \item{\dots}{at present, these are ignored.}
 }
 \value{
@@ -38,7 +39,7 @@
   This function is essentially a wrapper around the user-supplied \code{dprocess} slot of the \code{pomp} object.
   For specifications on writing such a function, see \code{\link{pomp}}.
 }
-\author{Aaron A. King (kingaa at umich dot edu)}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
 \seealso{\code{\link{pomp-class}}, \code{\link{pomp}}}
 \keyword{models}
 \keyword{ts}

Modified: pkg/man/euler.Rd
===================================================================
--- pkg/man/euler.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/euler.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -5,7 +5,8 @@
 \alias{onestep.density}
 \title{Plug-ins for dynamical models based on stochastic Euler algorithms}
 \description{
-  Facilities for implementing discrete-time Markov processes and continuous-time Markov processes using the Euler algorithm.
+  Plug-in facilities for implementing discrete-time Markov processes and continuous-time Markov processes using the Euler algorithm.
+  These can be used in the \code{rprocess} and \code{dprocess} slots of \code{pomp}.
 }
 \usage{
 euler.simulate(xstart, times, params, step.fun, delta.t, \dots,
@@ -36,42 +37,33 @@
     The \code{nrep} columns of \code{params} correspond to those of \code{xstart}.
   }
   \item{step.fun}{
-    This can be either an R function or a compiled, dynamically loaded native function containing the model simulator.
+    This can be either an R function or the name of a compiled, dynamically loaded native function containing the model simulator.
     It should be written to take a single Euler step from a single point in state space.
-    If it is a native function, it must be of type "pomp\_onestep\_sim" as defined in the header "pomp.h", which is included with the package.
+    If it is a native function, it must be of type \dQuote{pomp\_onestep\_sim} as defined in the header \dQuote{pomp.h}, which is included with the package.
     For details on how to write such codes, see Details.
   }
   \item{dens.fun}{
     This can be either an R function or a compiled, dynamically loaded native function containing the model transition log probability density function.
     This function will be called to compute the log likelihood of the actual Euler steps.
-    It must be of type "pomp\_onestep\_pdf" as defined in the header "pomp.h", which is included with the package.
+    It must be of type \dQuote{pomp\_onestep\_pdf} as defined in the header \dQuote{pomp.h}, which is included with the package.
     For details on how to write such codes, see Details.
   }
   \item{delta.t}{
     Time interval of Euler steps.
   }
-  \item{statenames}{
-    Names of state variables, in the order they will be expected by the routine named in \code{step.fun} and \code{dens.fun}.
+  \item{statenames, paramnames, covarnames}{
+    Names of state variables, parameters, covariates, in the order they will be expected by the routine named in \code{step.fun} and \code{dens.fun}.
+    This information is only used when the latter are implemented as compiled native functions.
   }
-  \item{paramnames}{
-    Names of parameters, in the order they will be expected by the routine named in \code{step.fun} and \code{dens.fun}.
-  }
-  \item{covarnames}{
-    Names of columns of the matrix of covariates \code{covar}, in the order they will be expected by the routine named in \code{step.fun} and \code{dens.fun}.
-  }
   \item{zeronames}{
     Names of additional variables which will be zeroed before each time in \code{times}.
     These are useful, e.g., for storing accumulations of state variables.
   }
-  \item{tcovar}{
-    Times at which covariates are measured.
+  \item{covar, tcovar}{
+    Matrix of covariates and times at which covariates are measured.
   }
-  \item{covar}{
-    Matrix of covariates.
-    This should have dimensions \code{length(tcovar)} x \code{ncovar}, where \code{ncovar} is the number of covariates.
-  }
   \item{log}{
-    logical; if TRUE, probabilities p are given as log(p).
+    logical; if TRUE, log probabilities are given.
   }
   \item{\dots}{
     if \code{step.fun} (or \code{dens.fun}) is an R function, then additional arguments will be passed to it.
@@ -113,7 +105,7 @@
   \code{onestep.density} returns a \code{nrep} x \code{ntimes-1} array.
   If \code{f} is this array, \code{f[i,j]} is the likelihood of a transition from \code{x[,i,j]} to \code{x[,i,j+1]} in exactly one Euler step of duration \code{times[j+1]-times[j]}.
 }
-\author{Aaron A. King (kingaa at umich dot edu)}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
 \seealso{\code{\link{eulermultinom}}, \code{\link{pomp}}}
 \examples{
 ## an example showing how to use these functions to implement a seasonal SIR model is contained

Modified: pkg/man/euler.sir.Rd
===================================================================
--- pkg/man/euler.sir.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/euler.sir.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -6,8 +6,6 @@
   \code{euler.sir} is a \code{pomp} object encoding a simple seasonal SIR model.
 }
 \usage{data(euler.sir)}
-\details{
-}
 \examples{
 data(euler.sir)
 plot(euler.sir)

Modified: pkg/man/eulermultinom.Rd
===================================================================
--- pkg/man/eulermultinom.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/eulermultinom.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -4,20 +4,23 @@
 \alias{deulermultinom}
 \title{Euler-multinomial models}
 \description{
-  Density and random generation for the Euler-multinomial death process with parameters \code{size}, \code{rate}, and \code{dt}.
+  Density and random-deviate generation for the Euler-multinomial death process with parameters \code{size}, \code{rate}, and \code{dt}.
 }
 \usage{
 reulermultinom(n = 1, size, rate, dt)
 deulermultinom(x, size, rate, dt, log = FALSE)
 }
 \arguments{
-  \item{n}{Number of random variates to generate.}
-  \item{size}{Number of individuals at risk.}
-  \item{rate}{Hazard rates.}
-  \item{dt}{Duration of Euler step.}
+  \item{n}{integer; number of random variates to generate.}
+  \item{size}{scalar integer; number of individuals at risk.}
+  \item{rate}{numeric vector of hazard rates.}
+  \item{dt}{numeric scalar; duration of Euler step.}
   \item{x}{Matrix or vector containing number of individuals that have succumbed to each death process.}
-  \item{log}{logical; if TRUE, return logarithm of probabilities.}
+  \item{log}{logical; if TRUE, return logarithm(s) of probabilities.}
 }
+\details{
+  Direct access to the underlying C routines is available: see the header file \dQuote{pomp.h}, included with the package.
+}
 \value{
   \item{reulermultinom}{
     Returns a \code{length(rate)} by \code{n} matrix.
@@ -25,15 +28,11 @@
     Each row contains the numbers of individuals succumbed to the corresponding process.
   }
   \item{deulermultinom}{
-    Returns a vector (of length equal to the number of columns of \code{x}) containing the probabilities of observing \code{x} given the specified parameters (\code{size}, \code{rate}, \code{dt}).
+    Returns a vector (of length equal to the number of columns of \code{x}) containing the probabilities of observing each column of \code{x} given the specified parameters (\code{size}, \code{rate}, \code{dt}).
   }
 }
-\details{
-  Direct access to the underlying C routines is available: see the header file "pomp.h", included with the package,
-  e.g., \code{edit(file=system.file("include/pomp.h",package="pomp"))}.
-}
-\author{Aaron A. King (kingaa at umich dot edu)}
-\seealso{\code{\link{euler}}, \code{\link{pomp}}}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
+\seealso{\code{\link{euler}}}
 \examples{
 print(x <- reulermultinom(5,size=100,rate=c(a=1,b=2,c=3),dt=0.1))
 deulermultinom(x,size=100,rate=c(1,2,3),dt=0.1)

Modified: pkg/man/init.state-pomp.Rd
===================================================================
--- pkg/man/init.state-pomp.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/init.state-pomp.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -3,12 +3,11 @@
 \alias{init.state}
 \alias{init.state,pomp-method}
 \alias{init.state-pomp}
-
-\title{
-  Return a matrix of initial conditions given a vector of parameters and an initial time.
-}
+\title{Return a matrix of initial conditions given a vector of parameters and an initial time.}
 \description{
   The method \code{init.state} returns a vector of initial conditions for the state process when given a vector of parameters \code{params} and an initial time \code{t0}.
+  This function is part of the low-level interface to \code{pomp} objects.
+  This help page does not give instructions on the implementation of models: see \code{\link{pomp}} for instructions.
 }
 \usage{
 init.state(object, params, t0, \dots)
@@ -25,8 +24,7 @@
 \value{
   Returns a matrix of initial states (with rownames).
 }
-\references{}
-\author{Aaron A. King (kingaa at umich dot edu)}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
 \seealso{\code{\link{pomp-class}}}
 \keyword{models}
 \keyword{ts}

Modified: pkg/man/mif-class.Rd
===================================================================
--- pkg/man/mif-class.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/mif-class.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -3,11 +3,11 @@
 \alias{mif-class}
 \title{The "mif" class}
 \description{
-  The MIF algorithm: maximum likelihood via iterated filtering.
-  The \code{mif} class holds a fitted model.
+  The \code{mif} class holds a fitted model and is created by a call to \code{\link{mif}}.
+  See \code{\link{mif}} for usage.
 }
 \section{Objects from the Class}{
-  Objects can be created by calls to the \code{mif} method on an \code{pomp} object.
+  Objects can be created by calls to the \code{\link{mif}} method on an \code{\link{pomp}} object.
   Such a call uses the MIF algorithm to fit the model parameters.
 }
 \section{Slots}{
@@ -28,7 +28,6 @@
     \item{particles}{
       A function of prototype \code{particles(Np,center,sd,...)} that draws particles from a distribution centered on \code{center} and with width proportional to \code{sd}.
       This function can be optionally specified by the user.
-      Its default value is a multivariate normal distribution with mean at \code{center} and standard deviation \code{sd}.
     }
     \item{alg.pars}{
       A named list of algorithm parameters.
@@ -36,11 +35,10 @@
       \code{Np}, the number of particles to use in filtering; 
       \code{var.factor}, the scaling coefficient relating the width of the initial particle distribution to \code{rw.sd};
       \code{ic.lag}, the fixed lag used in the estimation of initial-value parameters (IVPs);
-      and \code{cooling.factor}, the exponential cooling factor, \code{alpha}, where \code{0<alpha<1}.
+      and \code{cooling.factor}, the exponential cooling factor, where \code{0<cooling.factor<1}.
     }
     \item{random.walk.sd}{
       A named vector containing the random-walk variance to be used for ordinary parameters.
-      The width of the initial distribution of particles will be random.walk.sd*var.factor.
     }
     \item{pred.mean}{
       Matrix of prediction means.
@@ -63,7 +61,7 @@
       See \code{\link{pfilter}}.
     }
     \item{conv.rec}{
-      The "convergence record": a matrix containing a record of the parameter values, log likelihoods, and other pertinent information, with one row for each MIF iteration.
+      The \dQuote{convergence record}: a matrix containing a record of the parameter values, log likelihoods, and other pertinent information, with one row for each MIF iteration.
     }
     \item{loglik}{
       A numeric value containing the value of the log likelihood, as evaluated for the random-parameter model.
@@ -93,7 +91,7 @@
   Inapparent infections and cholera dynamics,
   Nature, 454:877--880, 2008.
 }
-\author{Aaron A. King (kingaa at umich dot edu)}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
 \seealso{\code{\link{mif}}, \link{mif-methods}, \code{\link{pomp}}, \link{pomp-class}}
 \keyword{models}
 \keyword{ts}

Modified: pkg/man/mif-methods.Rd
===================================================================
--- pkg/man/mif-methods.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/mif-methods.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -54,7 +54,7 @@
     }
     \item{mif}{
       Re-runs the MIF iterations.
-      See the documentation under \cite{Re-running MIF Iterations} below.
+      See the documentation for \code{\link{mif}}.
     }
     \item{compare.mif}{
       Given a \code{mif} object or a list of \code{mif} objects, \code{compare.mif} produces a set of diagnostic plots.
@@ -101,7 +101,7 @@
   Inapparent infections and cholera dynamics,
   Nature, 454:877--880, 2008.
 }
-\author{Aaron A. King (kingaa at umich dot edu)}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
 \seealso{\code{\link{mif}}, \code{\link{pomp}}, \code{\link{pomp-class}}, \code{\link{pfilter}}}
 \keyword{models}
 \keyword{ts}

Modified: pkg/man/mif.Rd
===================================================================
--- pkg/man/mif.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/mif.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -72,6 +72,7 @@
   \item{var.factor}{
     a positive number;
     the scaling coefficient relating the width of the initial particle distribution to \code{rw.sd}
+    The width of the initial distribution of particles will be \code{random.walk.sd*var.factor}.
   }
   \item{cooling.factor}{
     a positive number not greater than 1;
@@ -103,7 +104,7 @@
 \section{Re-running MIF Iterations}{
   To re-run a sequence of MIF iterations, one can use the \code{mif} method on a \code{mif} object.
   The call sequence is \code{mif(object)}.
-  By default, the same parameters used for the original MIF run are re-used.
+  By default, the same parameters used for the original MIF run are re-used (except for \code{weighted}, \code{tol}, \code{warn}, \code{max.fail}, and \code{verbose}, the defaults of which are shown above).
   If one does specify additional arguments, these will override the defaults.
 }
 \section{Continuing MIF Iterations}{
@@ -115,17 +116,18 @@
   Additional arguments will override the defaults.
 }
 \section{Details}{
+  If \code{particles} is not specified, the default behavior is to draw the particles from a multivariate normal distribution.
   \strong{It is the user's responsibility to ensure that, if the optional \code{particles} argument is given, that the \code{particles} function satisfies the following conditions:}
 
   \code{particles} has at least the following arguments:
   \code{Np}, \code{center}, \code{sd}, and \code{\dots}.
-  \code{Np} should be assumed to be an integer; \code{center} and \code{sd} will be named vectors of the same length.
+  \code{Np} may be assumed to be a positive integer;
+  \code{center} and \code{sd} will be named vectors of the same length.
   Additional arguments may be specified;
   these will be filled with the elements of the \code{userdata} slot of the underlying \code{pomp} object (see \code{\link{pomp-class}}).
 
-  \code{particles} returns a \code{length(center)} x \code{Np} matrix with rownames.
+  \code{particles} returns a \code{length(center)} x \code{Np} matrix with rownames matching the names of \code{center} and \code{sd}.
   Each column represents a distinct particle.
-  The rownames are used by the algorithms (see \code{mif}, \code{pfilter}).
 
   The center of the particle distribution returned by \code{particles} should be \code{center}.
   The width of the particle distribution should vary monotonically with \code{sd}.
@@ -140,10 +142,10 @@
   Inapparent infections and cholera dynamics,
   Nature, 454:877--880, 2008.
 }
-\author{Aaron A. King (kingaa at umich dot edu)}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
 \seealso{
   \code{\link{mif-class}}, \code{\link{mif-methods}}, \code{\link{pomp}}, \code{\link{pomp-class}}, \code{\link{pfilter}}.
-  See the "intro\_to\_pomp" vignette for an example.
+  See the \dQuote{intro\_to\_pomp} vignette for an example.
 }
 \keyword{models}
 \keyword{ts}

Modified: pkg/man/nlf.Rd
===================================================================
--- pkg/man/nlf.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/nlf.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -3,12 +3,12 @@
 \title{Fit Model to Data Using Nonlinear Forecasting (NLF)}
 \description{
   Calls an optimizer to maximize the nonlinear forecasting (NLF) goodness of fit, by simulating data from a model, fitting a nonlinear autoregressive model to the simulated time series (which may be multivariate) and using the fitted model to predict some or all variables in the data time series.
-  NLF is an 'indirect inference' method using a quasi-likelihood as the objective function.
+  NLF is an \sQuote{indirect inference} method using a quasi-likelihood as the objective function.
 }
 \usage{
  nlf(object, start, est, lags, period = NA, tensor = FALSE,
      nconverge=1000, nasymp=1000, seed = 1066, nrbf = 4,
-     method = 'subplex', skip.se = FALSE, verbose = FALSE, gr = NULL,
+     method = "subplex", skip.se = FALSE, verbose = FALSE, gr = NULL,
      bootstrap=FALSE, bootsamp = NULL,
      lql.frac = 0.1, se.par.frac = 0.1, eval.only = FALSE, \dots)
 }
@@ -76,14 +76,14 @@
     logical; if \code{TRUE}, no optimization is attempted and the quasi-loglikelihood value is evaluated at the \code{start} parameters.
   } 
   \item{\dots}{
-    Arguments that will be passed to \code{optim} in the \code{control} list.
+    Arguments that will be passed to \code{optim} or \code{subplex} in the \code{control} list.
   }
 }
 \details{
   This is functionally a wrapper for \code{nlf.objfun}, which does the statistical heavy lifting and should be consulted for details.
 }
 \value{
-  A list corresponding to the output from the optimizer, except that the full parameter vector is returned (not just the ones fitted), the LQL (and not -LQL) is reported, xstart is included, and asymptotic Wald standard errors based on M-estimator theory are returned for each fitted parameter.
+  A list corresponding to the output from the optimizer, except that the full parameter vector is returned (not just the ones fitted), the log quasilikelihood (LQL) (\emph{not} -LQL) is reported, xstart is included, and asymptotic Wald standard errors based on M-estimator theory are returned for each fitted parameter.
 }
 \references{
  The following papers describe and motivate the NLF approach to model fitting:
@@ -102,7 +102,7 @@
  \emph{Ecological Monographs} \bold{75}, 259--276.
  Available online at \url{http://repositories.cdlib.org/postprints/818/}
 }
-\author{Stephen P. Ellner (spe2 at cornell dot edu) and Bruce E. Kendall (kendall at bren dot ucsb dot edu)}
+\author{Stephen P. Ellner \email{spe2 at cornell dot edu} and Bruce E. Kendall \email{kendall at bren dot ucsb dot edu}}
 \keyword{models}
 \keyword{ts}
 

Modified: pkg/man/ou2.Rd
===================================================================
--- pkg/man/ou2.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/ou2.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -3,7 +3,7 @@
 \docType{data}
 \title{Two-dimensional Ornstein-Uhlenbeck process}
 \description{
-  \code{ou2} is a \code{pomp} object encoding a 2-D Ornstein-Uhlenbeck process.
+  \code{ou2} is a \code{pomp} object encoding a bivariate Ornstein-Uhlenbeck process.
 }
 \usage{data(ou2)}
 \details{
@@ -15,6 +15,7 @@
 \examples{
 data(ou2)
 plot(ou2)
+coef(ou2)
 p <- c(
        alpha.1=0.9,alpha.2=0,alpha.3=0,alpha.4=0.99,
        sigma.1=1,sigma.2=0,sigma.3=2,

Modified: pkg/man/particles-mif.Rd
===================================================================
--- pkg/man/particles-mif.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/particles-mif.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -4,13 +4,18 @@
 \alias{particles,mif-method}
 \alias{particles-mif}
 \title{Generate particles from the user-specified distribution.}
-\description{Generate particles from the user-specified distribution.}
+\description{
+  Generate particles from the user-specified distribution.
+  This is part of the low-level interface, used by \code{\link{mif}}.
+  This help page does not give instruction on how to write a valid \code{particles} function:
+  see the documentation for \code{\link{mif}} instead.
+}
 \usage{
 particles(object, \dots)
 \S4method{particles}{mif}(object, Np = 1, center = coef(object), sd = 0, \dots)
 }
 \arguments{
-  \item{object}{the "mif" object}
+  \item{object}{the \code{mif} object}
   \item{Np}{the number of particles, i.e., number of draws.}
   \item{center}{the central value of the distribution of particles}
   \item{sd}{the width of the distribution}
@@ -19,15 +24,14 @@
 \details{
   The \code{particles} method is used to set up the initial distribution
   of particles.  It is an interface to the user-specifed
-  \code{particles} slot in the "mif" object.
+  \code{particles} slot in the \code{mif} object.
 }
 \value{
   \code{particles} returns a list of two matrices.  \code{states}
   contains the state-variable portion of the particles; \code{params}
   contains the parameter portion.  Each has \code{Np} columns.
 }
-\author{Aaron A. King (kingaa at umich dot edu)}
-\seealso{\code{\link{mif}}, \link{mif-methods}, \code{\link{pomp}},
-  \link{pomp-class}}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
+\seealso{\code{\link{mif}}, \link{mif-methods}, \code{\link{pomp}}, \link{pomp-class}}
 \keyword{models}
 \keyword{ts}

Modified: pkg/man/pfilter.Rd
===================================================================
--- pkg/man/pfilter.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/pfilter.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -6,7 +6,8 @@
 \alias{pfilter-mif}
 \title{Particle filter}
 \description{
-  Run a particle filter.
+  Run a plain vanilla particle filter.
+  Resampling is performed after each observation.
 }
 \usage{
 pfilter(object, \dots)
@@ -22,7 +23,7 @@
     An object of class \code{pomp} or inheriting class \code{pomp}.
   }
   \item{params}{
-    A \code{npars} x \code{np} matrix containing the parameters corresponding to the initial state values in \code{xstart}.
+    A \code{npars} x \code{Np} matrix containing the parameters corresponding to the initial state values in \code{xstart}.
     This must have a 'rownames' attribute.
     It is permissible to supply \code{params} as a named numeric vector, i.e., without a \code{dim} attribute.
     In this case, all particles will inherit the same parameter values.
@@ -92,7 +93,7 @@
   A Tutorial on Particle Filters for Online Nonlinear, Non-Gaussian Bayesian Tracking.
   IEEE Trans. Sig. Proc. 50:174--188, 2002.
 }
-\author{Aaron A. King (kingaa at umich dot edu)}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
 \seealso{\link{pomp-class}}
 \keyword{models}
 \keyword{ts}

Modified: pkg/man/pomp-class.Rd
===================================================================
--- pkg/man/pomp-class.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/pomp-class.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -2,11 +2,13 @@
 \docType{class}
 \alias{pomp-class}
 \title{Partially-observed Markov process}
-\description{The class \code{pomp} encodes a partially-observed Markov process.}
+\description{
+  The class \code{pomp} encodes a partially-observed Markov process.
+  This page documents the structure of the class:
+  see the documentation for \code{\link{pomp}} for usage instructions.
+}
 \section{Objects from the Class}{
-  Objects should be created by calls of the function
-  \code{pomp}.  See the documentation for \code{\link{pomp}} for
-  usage instructions and important warnings.
+  Objects should be created by calls of the function \code{pomp}.
 }
 \section{Slots}{
   \describe{
@@ -26,16 +28,16 @@
       Function of prototype \code{dprocess(x,times,params,log=FALSE,\dots)} which evaluates the likelihood of a sequence of consecutive state transitions.
     }
     \item{dmeasure}{
-      an object of class "pomp.fun" which encodes the measurement model density.
+      an object of class \dQuote{pomp.fun} which encodes the measurement model density.
     }
     \item{rmeasure}{
-      an object of class "pomp.fun" which encodes the measurement model simulator.
+      an object of class \dQuote{pomp.fun} which encodes the measurement model simulator.
     }
     \item{skeleton.type}{
       a character variable specifying whether the deterministic skeleton is a map or a vectorfield.
     }
     \item{skeleton}{
-      an object of class "pomp.fun" which encodes the deterministic skeleton.
+      an object of class \dQuote{pomp.fun} which encodes the deterministic skeleton.
     }
     \item{initializer}{
       Function of prototype \code{initializer(params,t0,\dots)} which gives a vector of initial conditions when given a vector of parameters, \code{params}, and a time \code{t0}.
@@ -65,7 +67,7 @@
 \section{Methods}{
   See the pomp methods documentation: \link{pomp-methods}.
 }
-\author{Aaron A. King (kingaa at umich dot edu)}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
 \seealso{
   \code{\link{pomp}},
   \link{pomp-methods},

Modified: pkg/man/pomp-methods.Rd
===================================================================
--- pkg/man/pomp-methods.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/pomp-methods.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -62,7 +62,7 @@
     name of the class to which \code{object} should be coerced.
   }
   \item{from, to}{
-    the classes betwen which coercion should be performed.
+    the classes between which coercion should be performed.
   }
   \item{strict}{
     ignored.
@@ -73,7 +73,7 @@
     names of variables to plot.
   }
   \item{panel}{
-    a 'function(x, col, bg, pch, type, ...)' which gives the action to be carried out in each panel of the display.
+    a function of prototype \code{panel(x, col, bg, pch, type, ...)} which gives the action to be carried out in each panel of the display.
   }
   \item{nc}{
     the number of columns to use.
@@ -114,7 +114,7 @@
     }
     \item{data.array}{
       \code{data.array(object)} returns the array of observations.
-      \code{data.array(object,vars)} gives just the observations of variables \code{vars}.
+      \code{data.array(object,vars)} gives just the observations of variables named \code{vars}.
       \code{vars} may specify the variables by position or by name.
     }
     \item{states}{
@@ -168,7 +168,7 @@
     }
   }
 }
-\author{Aaron A. King (kingaa at umich dot edu)}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
 \seealso{
   \code{\link{pomp}},
   \link{pomp-class},

Modified: pkg/man/pomp-package.Rd
===================================================================
--- pkg/man/pomp-package.Rd	2009-06-01 17:30:52 UTC (rev 137)
+++ pkg/man/pomp-package.Rd	2009-06-02 19:20:25 UTC (rev 138)
@@ -3,31 +3,29 @@
 \alias{pomp-package}
 \title{Partially-observed Markov processes}
 \description{
-  The \code{pomp} package provides facilities for inference using partially-observed Markov processes (AKA state-space models or nonlinear stochastic dynamical systems).
-  The user provides functions specifying some or all of the model's process and measurement components.
-  The package's algorithms are built on top of these functions.
+  The \code{pomp} package provides facilities for inference on time series data using partially-observed Markov processes (AKA state-space models or nonlinear stochastic dynamical systems).
+  The user encodes a model as a \code{\link{pomp}} object by providing functions specifying some or all of the model's process and measurement components.
+  The package's algorithms for fitting models to data, simulating, etc. then call these functions.
   At the moment, algorithms are provided for
-  particle filtering (AKA sequential Monte Carlo or sequential importance sampling),
-  the likelihood maximization by iterated filtering (MIF) method of Ionides, Breto, and King (PNAS, 103:18438-18443, 2006),
-  and the nonlinear forecasting algorithm of Kendall, Ellner, et al. (Ecol. Monog. 75:259-276, 2005).
+  particle filtering (AKA sequential Monte Carlo or sequential importance sampling, see \code{\link{pfilter}}),
+  the likelihood maximization by iterated filtering (\acronym{MIF}) method of Ionides, Breto, and King (PNAS, 103:18438-18443, 2006, see \code{\link{mif}}),
+  and the nonlinear forecasting algorithm of Kendall, Ellner, et al. (Ecol. Monog. 75:259-276, 2005, see \code{\link{nlf}}).
   Future support for a variety of other algorithms is envisioned.
-  A working group of the National Center for Ecological Analysis and Synthesis (NCEAS), "Inference for Mechanistic Models", is currently implementing additional methods for this package.
[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/pomp -r 138


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