#' @title Summarise the output of the BMEA MCMC process
#'
#' @description Takes the kept simulations from a BMEA MCMC process and provides the summary statistics.
#'
#' @details
#' Provides summary statistics, quantiles & convergence statistics for a BMEA.MCMC object.
#'
#' To approximate normality, sigma_mu, sigma_p & sigma_S are log transformed when calculating rHat.
#' If \code{transform = TRUE}, all S simulations are log transformed & phi simulations are logit transformed.
#' If the mixture prior for phi has been used, this should be set to \code{FALSE} as values of zero
#' or one will be possible & will not be suitable for transformation.
#'
#' @param data an object of class BMEA.MCMC
#' @param transform logical. If \code{transform = TRUE}, the S & phi simulations will be transformed to the
#' log & logit scales respectively when calculating the convergence statistics.
#'
#' @return A matrix with columns containing the mean, sd, quantiles (0.025, 0.25, 0.50, 0.75, 0.975), rHat &
#' nEff for each BMEA model parameter.
#'
#' @references
#' Brooks, S.P. and Gelman, A. (1998)
#' \emph{General Methods for Monitoring Convergence of Iterative Simulations}
#' Journal of Computational and Graphical Statistics, Vol. 7, No. 4 (Dec), pp. 434-455
#'
#' @useDynLib BMEA summariseMCMC
#'
#' @export
summariseChains <- function(data, transform=TRUE) {
# data must be the output from a BMEA run, with class BMEA.MCMC
# transform indicates whether to logit transform phi & log transform S when calculating convergence statistics
# returns a matrix with the summary statistics
if (class(data)!="BMEA.MCMC") stop("The object must be of class 'BMEA.MCMC'\n")
out <- .Call("summariseMCMC",data, transform, PACKAGE="BMEA") # TRUE indicates logit transformation for phi, FALSE will disable this feature
return(out)
}
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