R/package.R

In cbreto/panelPomp: Inference for Panel Partially Observed Markov Processes

## package description

#' @docType package
#' @name panelPomp-package
#' @title Inference for PanelPOMPs (Panel Partially Observed Markov Processes)
#'
#' @description The \pkg{panelPomp} package provides facilities for inference
#' on panel data using panel partially-observed Markov process
#' (\acronym{PanelPOMP}) models. To do so, it relies on and extends a number
#' of facilities that the \pkg{pomp} package provides for inference on time
#' series data using partially-observed Markov process (\acronym{POMP}) models.
#'
#' The \pkg{panelPomp} package extends to panel data some of the capabilities
#' of the \pkg{pomp} package to fit nonlinear, non-Gaussian dynamic models.
#' This is done accomodating both fixed and random effects. Currently, the
#' focus is on likelihood-based approaches. In addition to these
#' likelihood-based tools, \pkg{panelPomp} also provides a framework under
#' which alternative statistical methods for \acronym{PanelPOMP} models can be
#' developed (very much like \pkg{pomp} provides a platform upon which
#' statistical inference methods for \acronym{POMP} models can be implemented).
#'
#' @section Data analysis using \pkg{panelPomp}:
#' The first step in using \pkg{panelPomp} is to encode one's model(s) and data
#'  in objects of class \code{panelPomp}.
#' One does this via a call to the \link[=panelPomp]{panelPomp} constructor
#' function.
#'
#' \pkg{panelPomp} version
#' \Sexpr[echo=FALSE,stage=build,results=text]{packageDescription("panelPomp",fields="Version")}
#' provides algorithms for
#' \enumerate{
#' \item particle filtering of panel data (AKA sequential Monte Carlo or
#' sequential importance sampling), as proposed in \Breto, Ionides and King
#' (2020). This reference provides the fundamental theoretical support for the
#' averaging of Monte Carlo replicates of panel unit likelihoods as implemented
#' in \pkg{panelPomp}; see \code{\link{pfilter}}
#' \item the panel iterated filtering method of \Breto, Ionides and King
#' (2020). This reference provides the fundamental theoretical support for the
#' extensions of the iterated filtering ideas of Ionides et al. (2006, 2011,
#' 2015) to panel data as implemented in \pkg{panelPomp}; see
#' \code{\link{mif2}}
#' }
#' The package also provides various tools for handling and extracting
#' information on models and data.
#'
#' @section Extending the \pkg{pomp} platform for developing inference tools:
#' \pkg{panelPomp} extends to panel data the general interface to the
#' components of \acronym{POMP} models provided by \pkg{pomp}. In doing so, it
#' contributes to the goal of the \pkg{pomp} project of facilitating the
#' development of new algorithms in an environment where they can be tested
#' and compared on a growing body of models and datasets.
#'
#' @section Comments, bug reports, and requests:
#' Contributions are welcome, as are suggestions for improvement, feature
#' requests, and bug reports.
#' Please submit these via the \href{https://github.com/cbreto/panelPomp/issues}{panelPomp issues page}.
#' We particularly welcome minimal working examples displaying uninformative,
#' misleading or inacurate error messages. We also welcome suggestions for
#' clarifying obscure passages in the documentation. Help requests are welcome,
#' but please consider before sending requests whether they are regarding the
#' use of \pkg{panelPomp} or that of \pkg{pomp}. For help with \pkg{pomp},
#' please visit
#' \href{https://kingaa.github.io/pomp/FAQ.html#how-can-i-submit-an-effective-request-for-help}{\pkg{pomp}'s FAQ}.
#'
#' @section Documentation:
#' Examples are provided via the \code{contacts()}, \code{panelGompertz()}
#' and \code{panelRandomWalk()} functions.
#'
#' @section License:
#' \pkg{panelPomp} is provided under the GPL-3 License.
#'
#' @references \breto2020
#' @author Carles \Breto
#'
#' @seealso \link[=pomp-package]{pomp package}, \link{panelPomp}
#'
#' @keywords models datasets ts
#'
#' @import methods
#' @import pomp
# @useDynLib panelPomp, .registration=TRUE
#' @importFrom stats dnorm runif setNames var
#' @importFrom utils tail read.table
NULL        # replacing NULL by "_PACKAGE" results in roxygen2 adding an
            # \alias{} with the package name, conflicting with functions named
            # after the package

pStop <- function (fn, ...) {
  fn <- as.character(fn) # nocov
  stop("in ",sQuote(fn[1L]),": ",...,call.=FALSE) #nocov
}

pStop_ <- function (...) {
  stop(...,call.=FALSE) #nocov
}