R/BayesianTools.R

#' @title BayesianTools
#' @name BayesianTools
#' @docType package
#' @useDynLib BayesianTools, .registration = TRUE
#' @description A package with general-purpose MCMC and SMC samplers,  as well as plots and diagnostic functions for Bayesian statistics
#' @details A package with  general-purpose MCMC and SMC samplers, as well as plots and diagnostic functions for Bayesian statistics, particularly for process-based models. 
#' 
#' The package contains 2 central functions, \code{\link{createBayesianSetup}}, which creates a standardized Bayesian setup with likelihood and priors, and \code{\link{runMCMC}}, which allows to run various MCMC and SMC samplers.
#' 
#' The package can of course also be used for general (non-Bayesian) target functions. 
#' 
#' To use the package, a first step to use \code{\link{createBayesianSetup}} to create a BayesianSetup, which usually contains prior and likelihood densities, or in general a target function. 
#'
#' Those can be sampled with \code{\link{runMCMC}}, which can call a number of general purpose Metropolis sampler, including the \code{\link{Metropolis}} that allows to specify various popular Metropolis variants such as adaptive and/or delayed rejection Metropolis; two variants of differential evolution MCMC \code{\link{DE}}, \code{\link{DEzs}}, two variants of DREAM  \code{\link{DREAM}} and \code{\link{DREAMzs}}, the \code{\link{Twalk}} MCMC, and a Sequential Monte Carlo sampler \code{\link{smcSampler}}. 
#'
#' The output of runMCMC is of class mcmcSampler / smcSampler if one run is performed, or mcmcSamplerList / smcSamplerList if several sampler are run. Various functions are available for plotting, model comparison (DIC, marginal likelihood), or to use the output as a new prior.  
#'
#' For details on how to use the packgage, run vignette("BayesianTools", package="BayesianTools").
#' 
#' To get the suggested citation, run citation("BayesianTools")
#'
#' To report bugs or ask for help, post a \href{http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example}{reproducible example} via the BayesianTools \href{https://github.com/florianhartig/BayesianTools/issues}{issue tracker} on GitHub. 
#'
#'Acknowledgements: The creation and maintenance of this package profited from funding and collaboration through Cost Action FP 1304 PROFOUND, DFG	DO 786/12-1 CONECT, EU FP7 ERA-NET Sumforest REFORCE and Bayklif Project BLIZ. 
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BayesianTools documentation built on Dec. 10, 2019, 1:08 a.m.