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#' Print method for summarizing InSilicoVA Model Fits
#'
#' This function is the print method for class \code{insilico}.
#'
#'
#' @param x \code{insilico} object.
#' @param ... not used
#'
#' @author Zehang Li, Tyler McCormick, Sam Clark
#'
#' Maintainer: Zehang Li <lizehang@@uw.edu>
#' @seealso \code{\link{summary.insilico}}
#' @references
#' Tyler H. McCormick, Zehang R. Li, Clara Calvert, Amelia C. Crampin,
#' Kathleen Kahn and Samuel J. Clark Probabilistic cause-of-death assignment
#' using verbal autopsies, \emph{Journal of the American Statistical
#' Association} (2016), 111(515):1036-1049.
#' @examples
#' \dontrun{
#' # load sample data together with sub-population list
#' data(RandomVA1)
#' # extract InterVA style input data
#' data <- RandomVA1$data
#' # extract sub-population information.
#' # The groups are "HIV Positive", "HIV Negative" and "HIV status unknown".
#' subpop <- RandomVA1$subpop
#'
#' # run without subpopulation
#' fit1<- insilico( data, subpop = NULL,
#' Nsim = 400, burnin = 200, thin = 10 , seed = 1,
#' external.sep = TRUE, keepProbbase.level = TRUE)
#' fit1
#' }
#' @export
print.insilico <- function(x,...){
cat("InSilicoVA fitted object:\n")
cat(paste(length(x$id), "death processed\n"))
cat(paste(x$Nsim, "iterations performed, with first",
x$burnin, "iterations discarded\n",
trunc((x$Nsim - x$burnin)/x$thin), "iterations saved after thinning\n"))
if(!x$updateCondProb){
cat("Fitted with fixed conditional probability matrix\n")
}else if(x$keepProbbase.level){
cat("Fitted with re-estimated InterVA4 conditional probability level table\n")
}else{
cat("Fitted with re-estimating InterVA4 conditional probability matrix\n")
}
}
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