R/print_insilico.r

Defines functions print.insilico

Documented in print.insilico

#' 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 <[email protected]@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{arXiv preprint arXiv:1411.3042}
#' \url{http://arxiv.org/abs/1411.3042} (2014)
#' @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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InSilicoVA documentation built on Sept. 21, 2018, 6:27 p.m.