[Pomp-commits] r1187 - pkg/pomp/man www/vignettes
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Fri Jun 5 18:10:05 CEST 2015
Author: kingaa
Date: 2015-06-05 18:10:04 +0200 (Fri, 05 Jun 2015)
New Revision: 1187
Added:
pkg/pomp/man/package.Rd
Removed:
pkg/pomp/man/pomp-package.Rd
Modified:
pkg/pomp/man/mif2.Rd
pkg/pomp/man/plugins.Rd
pkg/pomp/man/pomp.Rd
pkg/pomp/man/spect.Rd
www/vignettes/pomp.pdf
Log:
- fix up the help pages
Modified: pkg/pomp/man/mif2.Rd
===================================================================
--- pkg/pomp/man/mif2.Rd 2015-06-05 13:19:40 UTC (rev 1186)
+++ pkg/pomp/man/mif2.Rd 2015-06-05 16:10:04 UTC (rev 1187)
@@ -60,7 +60,7 @@
\item{start}{
named numerical vector;
the starting guess of the parameters.
- By default, \code{start=coef(object)}.
+ By default, \preformatted{start=coef(object).}
}
\item{Np}{
the number of particles to use in filtering.
Copied: pkg/pomp/man/package.Rd (from rev 1186, pkg/pomp/man/pomp-package.Rd)
===================================================================
--- pkg/pomp/man/package.Rd (rev 0)
+++ pkg/pomp/man/package.Rd 2015-06-05 16:10:04 UTC (rev 1187)
@@ -0,0 +1,76 @@
+\name{pomp-package}
+\title{Inference for partially observed Markov processes}
+\docType{package}
+\alias{The pomp package}
+\alias{pomp-package}
+\alias{pomp package}
+\description{
+ The \pkg{pomp} package provides facilities for inference on time series data using partially-observed Markov process (\acronym{POMP}) models.
+ These models are also known as state-space models or nonlinear stochastic dynamical systems.
+ One can use \pkg{pomp} to fit nonlinear, non-Gaussian dynamic models to time-series data.
+ The package is both a set of tools for data analysis and a platform upon which statistical inference methods for \acronym{POMP} models can be implemented.
+}
+\section{Data analysis using \pkg{pomp}}{
+ The first step in using \pkg{pomp} is to encode one's model(s) and data in objects of class \code{pomp}.
+ One does this via a call to \code{\link{pomp}}, which involves specifying the unobserved state process and the measurement process of the model.
+ Details on this are given in the documentation for the \code{\link{pomp}} constructor function.
+ Examples are given in the tutorials on the \href{http://pomp.r-forge.r-project.org}{package website}, in the demos (\code{demo(package='pomp')}), and via the \code{\link{pompExample}} function.
+
+ \pkg{pomp} version \Sexpr[echo=F,stage=install,results=text]{packageDescription("pomp",fields="Version")} provides algorithms for
+ \enumerate{
+ \item simulation of stochastic dynamical systems; see \code{\link[=simulate-pomp]{simulate}}
+ \item particle filtering (AKA sequential Monte Carlo or sequential importance sampling); see \code{\link{pfilter}}
+ \item the iterated filtering methods of Ionides et al. (2006, 2011, 2015);
+ see \code{\link{mif}} and \code{\link{mif2}}
+ \item the nonlinear forecasting algorithm of Kendall et al. (2005); see \code{\link{nlf}}
+ \item the particle MCMC approach of Andrieu et al. (2010); see \code{\link{pmcmc}}
+ \item the probe-matching method of Kendall et al. (1999, 2005); see \code{\link{probe.match}}
+ \item a spectral probe-matching method (Reuman et al. 2006, 2008); see \code{\link{spect.match}}
+ \item synthetic likelihood a la Wood (2010); see \code{\link{probe}}
+ \item approximate Bayesian computation (Toni et al. 2009); see \code{\link{abc}}
+ \item the approximate Bayesian sequential Monte Carlo scheme of Liu & West (2001); see \code{\link{bsmc}}
+ \item simple trajectory matching; see \code{\link{traj.match}}.
+ }
+ The package also provides various tools for plotting and extracting information on models and data.
+}
+\section{Developing inference tools on the \pkg{pomp} platform}{
+ \pkg{pomp} provides a very general interface to the components of \acronym{POMP} models.
+ All the inference algorithms in \pkg{pomp} interact with the models and data via this interface.
+ One goal of the \pkg{pomp} project has been to facilitate the development of new algorithms in an environment where they can be tested and compared on a growing body of models and datasets.
+
+ The low-level interface relevant to developers is documented \link[=rprocess]{here}.
+}
+\section{Comments, bug reports, feature requests}{
+ Contributions are welcome, as are comments, feature requests, and bug reports.
+ See the package website \url{http://pomp.r-forge.r-project.org} for more information, access to the package mailing list, links to the authors' websites, references to the literature, and up-to-date versions of the package source and documentation.
+}
+\section{Documentation}{
+ A number of tutorials, demonstrating the construction of \code{pomp} objects and the application of various inference algorithms, are available on the package homepage: \url{http://pomp.r-forge.r-project.org}.
+ Several examples of the construction of \code{pomp} objects are provided with the package and are documented in the help pages: to view a full list of these, execute \code{pompExample()}.
+ In addition, there are a number of demos, which can be viewed by executing \code{demo(package="pomp")}.
+}
+\section{History}{
+ Much of the groundwork for \pkg{pomp} was laid by a working group of the National Center for Ecological Analysis and Synthesis (\acronym{NCEAS}), \dQuote{Inference for Mechanistic Models}.
+}
+\section{License}{
+ \pkg{pomp} is provided under the \acronym{GNU} Public License (\acronym{GPL}).
+}
+\references{
+ See the package website, \url{http://pomp.r-forge.r-project.org}, for the references.
+}
+\author{Aaron A. King \email{kingaa at umich dot edu}}
+\seealso{
+ \code{\link{pomp}},
+ \link{pomp low-level interface},
+ \code{\link{pfilter}},
+ \code{\link[=simulate-pomp]{simulate}},
+ \code{\link{mif}},
+ \code{\link{nlf}},
+ \code{\link{probe}},
+ \code{\link{traj.match}},
+ \code{\link{bsmc2}},
+ \code{\link{pmcmc}}
+}
+\keyword{models}
+\keyword{datasets}
+\keyword{ts}
Modified: pkg/pomp/man/plugins.Rd
===================================================================
--- pkg/pomp/man/plugins.Rd 2015-06-05 13:19:40 UTC (rev 1186)
+++ pkg/pomp/man/plugins.Rd 2015-06-05 16:10:04 UTC (rev 1187)
@@ -31,7 +31,7 @@
\code{params} is a named numeric vector containing parameters,
and \code{delta.t} is the length of the Euler time-step.
- If \code{step.fun} is the name of a native function, it must be of type \code{pomp_onestep_sim} as defined in the header file \file{pomp.h}, which is included with the \pkg{pomp} package.
+ If \code{step.fun} is the name of a native function, it must be of type \preformatted{pomp_onestep_sim} as defined in the header file \file{pomp.h}, which is included with the \pkg{pomp} package.
Do \preformatted{file.show(system.file("include/pomp.h",package="pomp"))} to view this header file.
For details on how to write such codes, see Details.
}
@@ -44,7 +44,7 @@
For examples on the use of \code{\link{Csnippet}} to write fast simulators easily, see tutorials on the \href{http://pomp.r-forge.r-project.org}{package website}.
- If \code{rate.fun} is a native function, it must be of type \code{pomp_ssa_rate_fn} as defined in the header \file{pomp.h}, which is included with the package.
+ If \code{rate.fun} is a native function, it must be of type \preformatted{pomp_ssa_rate_fn} as defined in the header \file{pomp.h}, which is included with the package.
For details on how to write such codes, see Details.
}
\item{v, d}{
@@ -62,7 +62,7 @@
Here, \code{x1} and \code{x2} are named numeric vectors containing the values of the state process at times \code{t1} and \code{t2},
\code{params} is a named numeric vector containing parameters.
- If \code{dens.fun} is the name of a native function, it should be of type \code{pomp_onestep_pdf} as defined in the header \file{pomp.h}, which is included with the \pkg{pomp} package.
+ If \code{dens.fun} is the name of a native function, it should be of type \preformatted{pomp_onestep_pdf} as defined in the header \file{pomp.h}, which is included with the \pkg{pomp} package.
This function should return the log likelihood of a transition from \code{x1} at time \code{t1} to \code{x2} at time \code{t2}, assuming that no intervening transitions have occurred.
For details on how to write such codes, see Details.
}
@@ -101,7 +101,7 @@
This is accomplished via interpolation of the user-supplied covariate table.
Additional arguments may be given: these will be filled by the correspondingly-named elements in the \code{userdata} slot of the \code{pomp} object (see \code{\link{pomp}}).
- If \code{step.fun} is written in a native language, it must be a function of type \code{pomp_onestep_sim} as specified in the header \file{pomp.h} included with the package.
+ If \code{step.fun} is written in a native language, it must be a function of type \preformatted{pomp_onestep_sim} as specified in the header \file{pomp.h} included with the package.
Execute \preformatted{file.show(system.file("include/pomp.h",package="pomp.h"))} to view this file.
If \code{rate.fun} is written as an \R function, it must have at least the arguments \code{j}, \code{x}, \code{t}, \code{params}, and \code{\dots}.
@@ -110,7 +110,7 @@
\code{params} is a named vector containing parameters.
If the argument \code{covars} is included and a covariate table has been included in the \code{pomp} object, then on a call to this function, \code{covars} will be filled with the values, at time \code{t}, of the covariates.
This is accomplished via interpolation of the covariate table.
- If \code{rate.fun} is a native function, it must be of type \code{pomp_ssa_rate_fn} as defined in the header \file{pomp.h}; see above for instructions on how to view this file.
+ If \code{rate.fun} is a native function, it must be of type \preformatted{pomp_ssa_rate_fn} as defined in the header \file{pomp.h}; see above for instructions on how to view this file.
In writing \code{dens.fun}, you must assume that no state transitions have occurred between \code{t1} and \code{t2}.
If \code{dens.fun} is written as an \R function, it must have at least the arguments \code{x1}, \code{x2}, \code{t1}, \code{t2}, \code{params}, and \code{\dots}.
@@ -120,7 +120,7 @@
If the argument \code{covars} is included and a covariate table has been included in the \code{pomp} object, then on a call to this function, \code{covars} will be filled with the values, at time \code{t1}, of the covariates.
This is accomplished via interpolation of the covariate table.
As above, any additional arguments will be filled by the correspondingly-named elements in the \code{userdata} slot of the \code{pomp} object (see \code{\link{pomp}}).
- If \code{dens.fun} is written in a native language, it must be a function of type \code{pomp_onestep_pdf} as defined in the header \file{pomp.h} included with the package; see above for instructions on how to view this file.
+ If \code{dens.fun} is written in a native language, it must be a function of type \preformatted{pomp_onestep_pdf} as defined in the header \file{pomp.h} included with the package; see above for instructions on how to view this file.
}
\value{
\code{onestep.sim}, \code{euler.sim}, \code{discrete.time.sim}, and \code{gillespie.sim} each return functions suitable for use as the argument \code{rprocess} argument in \code{\link{pomp}}.
Deleted: pkg/pomp/man/pomp-package.Rd
===================================================================
--- pkg/pomp/man/pomp-package.Rd 2015-06-05 13:19:40 UTC (rev 1186)
+++ pkg/pomp/man/pomp-package.Rd 2015-06-05 16:10:04 UTC (rev 1187)
@@ -1,75 +0,0 @@
-\name{pomp-package}
-\title{Inference for partially observed Markov processes}
-\docType{package}
-\alias{The pomp package}
-\alias{pomp-package}
-\alias{pomp package}
-\description{
- The \pkg{pomp} package provides facilities for inference on time series data using partially-observed Markov process (\acronym{POMP}) models.
- These models are also known as state-space models or nonlinear stochastic dynamical systems.
- One can use \pkg{pomp} to fit nonlinear, non-Gaussian dynamic models to time-series data.
- The package is both a set of tools for data analysis and a platform upon which statistical inference methods for \acronym{POMP} models can be implemented.
-}
-\section{Data analysis using \pkg{pomp}}{
- The first step in using \pkg{pomp} is to encode one's model(s) and data in objects of class \code{pomp}.
- One does this via a call to \code{\link{pomp}}, which involves specifying the unobserved state process and the measurement process of the model.
- Details on this are given in the documentation for the \code{\link{pomp}} constructor function.
- Examples are given in the tutorials on the \href{http://pomp.r-forge.r-project.org}{package website}, in the demos (\code{demo(package='pomp')}), and via the \code{\link{pompExample}} function.
-
- \pkg{pomp} version \Sexpr[echo=F,stage=install,results=text]{packageDescription("pomp",fields="Version")} provides algorithms for
- \enumerate{
- \item simulation of stochastic dynamical systems; see \code{\link[=simulate-pomp]{simulate}}
- \item particle filtering (AKA sequential Monte Carlo or sequential importance sampling); see \code{\link{pfilter}}
- \item the iterated filtering method of Ionides et al. (2006, 2011, 2015); see \code{\link{mif}}
- \item the nonlinear forecasting algorithm of Kendall et al. (2005); see \code{\link{nlf}}
- \item the particle MCMC approach of Andrieu et al. (2010); see \code{\link{pmcmc}}
- \item the probe-matching method of Kendall et al. (1999, 2005); see \code{\link{probe.match}}
- \item a spectral probe-matching method (Reuman et al. 2006, 2008); see \code{\link{spect.match}}
- \item synthetic likelihood a la Wood (2010); see \code{\link{probe}}
- \item approximate Bayesian computation (Toni et al. 2009); see \code{\link{abc}}
- \item the approximate Bayesian sequential Monte Carlo scheme of Liu & West (2001); see \code{\link{bsmc}}
- \item simple trajectory matching; see \code{\link{traj.match}}.
- }
- The package also provides various tools for plotting and extracting information on models and data.
-}
-\section{Developing inference tools on the \pkg{pomp} platform}{
- \pkg{pomp} provides a very general interface to the components of \acronym{POMP} models.
- All the inference algorithms in \pkg{pomp} interact with the models and data via this interface.
- One goal of the \pkg{pomp} project has been to facilitate the development of new algorithms in an environment where they can be tested and compared on a growing body of models and datasets.
-
- The low-level interface relevant to developers is documented \link[=rprocess]{here}.
-}
-\section{Comments, bug reports, feature requests}{
- Contributions are welcome, as are comments, feature requests, and bug reports.
- See the package website \url{http://pomp.r-forge.r-project.org} for more information, access to the package mailing list, links to the authors' websites, references to the literature, and up-to-date versions of the package source and documentation.
-}
-\section{Documentation}{
- A number of tutorials, demonstrating the construction of \code{pomp} objects and the application of various inference algorithms, are available on the package homepage: \url{http://pomp.r-forge.r-project.org}.
- Several examples of the construction of \code{pomp} objects are provided with the package and are documented in the help pages: to view a full list of these, execute \code{pompExample()}.
- In addition, there are a number of demos, which can be viewed by executing \code{demo(package="pomp")}.
-}
-\section{History}{
- Much of the groundwork for \pkg{pomp} was laid by a working group of the National Center for Ecological Analysis and Synthesis (\acronym{NCEAS}), \dQuote{Inference for Mechanistic Models}.
-}
-\section{License}{
- \pkg{pomp} is provided under the \acronym{GNU} Public License (\acronym{GPL}).
-}
-\references{
- See the package website, \url{http://pomp.r-forge.r-project.org}, for the references.
-}
-\author{Aaron A. King \email{kingaa at umich dot edu}}
-\seealso{
- \code{\link{pomp}},
- \link{pomp low-level interface},
- \code{\link{pfilter}},
- \code{\link[=simulate-pomp]{simulate}},
- \code{\link{mif}},
- \code{\link{nlf}},
- \code{\link{probe}},
- \code{\link{traj.match}},
- \code{\link{bsmc2}},
- \code{\link{pmcmc}}
-}
-\keyword{models}
-\keyword{datasets}
-\keyword{ts}
Modified: pkg/pomp/man/pomp.Rd
===================================================================
--- pkg/pomp/man/pomp.Rd 2015-06-05 13:19:40 UTC (rev 1186)
+++ pkg/pomp/man/pomp.Rd 2015-06-05 16:10:04 UTC (rev 1187)
@@ -80,7 +80,7 @@
This can be specified in one of four ways:
\enumerate{
\item as a function of prototype \preformatted{rmeasure(x,t,params,\dots)} that makes a draw from the observation process given states \code{x}, time \code{t}, and parameters \code{params}.
- \item as the name of a native (compiled) routine with prototype \code{pomp_measure_model_simulator} as defined in the header file \file{pomp.h}.
+ \item as the name of a native (compiled) routine of type \preformatted{pomp_measure_model_simulator} as defined in the header file \file{pomp.h}.
(To view the header file, execute \preformatted{file.show(system.file("include/pomp.h",package="pomp"))} in an \R session.)
\item using the formula-based \code{measurement.model} facility (see below).
\item as a snippet of C code (via \code{\link{Csnippet}}) that draws from the observation process as above.
@@ -92,7 +92,7 @@
This can be specified in one of four ways:
\enumerate{
\item as a function of prototype \preformatted{dmeasure(y,x,t,params,log,\dots)} that computes the p.d.f. of \code{y} given \code{x}, \code{t}, and \code{params}.
- \item as the name of a native (compiled) routine with prototype \code{pomp_measure_model_density} as defined in the header file \file{pomp.h}.
+ \item as the name of a native (compiled) routine of type \preformatted{pomp_measure_model_density} as defined in the header file \file{pomp.h}.
(To view the header file, execute \preformatted{file.show(system.file("include/pomp.h",package="pomp"))} in an \R session.)
\item using the formula-based \code{measurement.model} facility (see below).
\item as a snippet of C code (via \code{\link{Csnippet}}) that computes the p.d.f. as above.
@@ -119,7 +119,7 @@
The skeleton function can be specified in one of three ways:
\enumerate{
\item as an \R function of prototype \preformatted{skeleton(x,t,params,\dots)} that evaluates the deterministic skeleton at state \code{x} and time \code{t} given the parameters \code{params},
- \item as the name of a native (compiled) routine with prototype \code{pomp_skeleton} as defined in the header file \file{pomp.h}.
+ \item as the name of a native (compiled) routine of type \preformatted{pomp_skeleton} as defined in the header file \file{pomp.h}.
(To view the header file, execute \preformatted{file.show(system.file("include/pomp.h",package="pomp"))} in an \R session.)
\item as a snippet of C code (via \code{\link{Csnippet}}) that performs this evaluation.
The latter is typically the preferred option, for reasons of computational efficiency.
@@ -137,7 +137,7 @@
This can be specified in one of three ways:
\enumerate{
\item as an \R function of prototype \preformatted{rprior(params,\dots)} that makes a draw from the prior distribution given \code{params},
- \item as the name of a native (compiled) routine with prototype \code{pomp_rprior} as defined in the header file \file{pomp.h}, or
+ \item as the name of a native (compiled) routine of type \preformatted{pomp_rprior} as defined in the header file \file{pomp.h}, or
(To view the header file, execute \preformatted{file.show(system.file("include/pomp.h",package="pomp"))} in an \R session.)
\item as a snippet of C code (via \code{\link{Csnippet}}).
}
@@ -148,7 +148,7 @@
This can be specified in one of three ways:
\enumerate{
\item as an \R function of prototype \preformatted{dprior(params,log=FALSE,\dots)} that evaluates the prior probability density,
- \item as the name of a native (compiled) routine with prototype \code{pomp_dprior} as defined in the header file \file{pomp.h}, or
+ \item as the name of a native (compiled) routine of type \preformatted{pomp_dprior} as defined in the header file \file{pomp.h}, or
(To view the header file, execute \preformatted{file.show(system.file("include/pomp.h",package="pomp"))} in an \R session.)
\item as a snippet of C code (via \code{\link{Csnippet}}).
}
@@ -187,7 +187,7 @@
When working with such an algorithm and a model for which the parameters are constrained, it can be useful to transform parameters.
\code{toEstimationScale} and \code{fromEstimationScale} are transformations from the model scale to the estimation scale, and vice versa, respectively.
These functions must have arguments \code{params} and \code{\dots}.
- \code{toEstimationScale} should transform parameters from the scale that \code{rprocess}, \code{dprocess}, \code{rmeasure}, \code{dmeasure}, \code{skeleton}, and \code{initializer} use internally to the scale used in estimation.
+ \code{toEstimationScale} should transform parameters from the scale that \code{rprocess}, \code{dprocess}, \code{rmeasure}, \code{dmeasure}, and \code{skeleton} use internally to the scale used in estimation.
\code{fromEstimationScale} should be the inverse of \code{toEstimationScale}.
The parameter transformations can be defined (as above) using either \R functions, native routines, or \code{\link{Csnippet}}s.
@@ -203,7 +203,7 @@
}
\item{globals}{
optional character;
- C code that will be included in the source for (and therefore hard-coded into) the shared-object library created when the call to \code{pomp} uses \code{Csnippets}.
+ C code that will be included in the source for (and therefore hard-coded into) the shared-object library created when the call to \code{pomp} uses \code{\link{Csnippet}}s.
If no \code{Csnippet}s are used, \code{globals} has no effect.
}
\item{\dots}{
@@ -277,7 +277,7 @@
}
\section{The observation process model}{
The following is a guide to writing the measurement model components as \R functions.
- For a description on how to write these components using \code{Csnippet}s, see the tutorials on the \href{http://pomp.r-forge.r-project.org}{package website}.
+ For a description on how to write these components using \code{\link{Csnippet}}s, see the tutorials on the \href{http://pomp.r-forge.r-project.org}{package website}.
\describe{
\item{\code{rmeasure}}{
if provided, must take at least the arguments \code{x}, \code{t}, \code{params}, and \code{\dots}.
@@ -304,7 +304,7 @@
}
\section{The deterministic skeleton}{
The following describes how to specify the deterministic skeleton as an \R function.
- For a description on how to write this component using \code{Csnippet}s, see the tutorials on the \href{http://pomp.r-forge.r-project.org}{package website}.
+ For a description on how to write this component using \code{\link{Csnippet}}s, see the tutorials on the \href{http://pomp.r-forge.r-project.org}{package website} and the \code{\link{Csnippet}} help.
If \code{skeleton} if provided, must have at least the arguments \code{x}, \code{t}, \code{params}, and \code{\dots}.
\code{x} is a numeric vector containing the coordinates of a point in state space at which evaluation of the skeleton is desired.
Modified: pkg/pomp/man/spect.Rd
===================================================================
--- pkg/pomp/man/spect.Rd 2015-06-05 13:19:40 UTC (rev 1186)
+++ pkg/pomp/man/spect.Rd 2015-06-05 16:10:04 UTC (rev 1187)
@@ -124,7 +124,7 @@
\item{detrend}{detrending option used.}
}
- \code{spect.match} returns an object of class \code{spect.matched.pomp}, which is derived from class \code{{spect.pomp}} and therefore has all the slots of that class.
+ \code{spect.match} returns an object of class \code{spect.matched.pomp}, which is derived from class \code{spect.pomp} and therefore has all the slots of that class.
In addition, \code{spect.matched.pomp} objects have the following slots:
\describe{
\item{est, weights, fail.value}{values of the corresponding arguments in the call to \code{spect.match}.}
Modified: www/vignettes/pomp.pdf
===================================================================
--- www/vignettes/pomp.pdf 2015-06-05 13:19:40 UTC (rev 1186)
+++ www/vignettes/pomp.pdf 2015-06-05 16:10:04 UTC (rev 1187)
@@ -1,33 +1,27 @@
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[TRUNCATED]
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