R/imports.R

#' @importFrom coda mcmc mcmc.list
#' @importFrom parallel makePSOCKcluster stopCluster clusterExport clusterEvalQ
#'   clusterApply detectCores clusterSetRNGStream
#' @importFrom methods formalArgs
#' @importFrom stats runif plogis
#' @importFrom MASS mvrnorm
#' @importFrom utils head ls.str
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#' A friendly MCMC framework
#' 
#' The `fmcmc` package provides a flexible framework for implementing MCMC models
#' using a lightweight in terms of dependencies. Among its main features, `fmcmc`
#' allows:
#' 
#' - Implementing arbitrary transition kernels.
#' 
#' - Incorporating convergence monitors for automatic stop.
#' 
#' - Out-of-the-box parallel computing implementation for running multiple chains
#' simultaneously.
#' 
#' For more information see the packages vignettes:
#' 
#' ```
#' vignette("workflow-with-fmcmc", "fmcmc")
#' 
#' vignette("user-defined-kernels", "fmcmc")
#' ```
#' 
#' @references
#' Vega Yon et al., (2019). fmcmc: A friendly MCMC framework. Journal of Open
#' Source Software, 4(39), 1427, \doi{10.21105/joss.01427}
#' 
#' @aliases fmcmc-package 
#' @name fmcmc
#' 
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fmcmc documentation built on Aug. 30, 2023, 1:09 a.m.