# R/print.summary.mrs.R In jacsor/MRS: Multi-Resolution Scanning for Cross-Sample Differences

#' Print summary of a mrs object
#'
#' This function print the summary the output of the \code{\link{mrs}} function.
#' It provides the marginal prior and posterior of the null and the top regions of the representative tree.
#'
#' @param x A \code{summary.mrs} object
#' @param ... Additional print parameters.
#' @references Soriano J. and Ma L. (2016).
#' Probabilistic multi-resolution scanning for two-sample differences.
#'  \emph{Journal of the Royal Statistical Society: Series B (Statistical Methodology)}.
#' @references Ma L. and Soriano J. (2016).
#' Analysis of distributional variation through multi-scale Beta-Binomial modeling.
#'  \emph{arXiv}.
#'  \url{http://arxiv.org/abs/1604.01443}
#' @export
#' @S3method summary mrs
#' @examples
#' set.seed(1)
#' n = 100
#' p = 2
#' X = matrix(c(runif(p*n/2),rbeta(p*n/2, 1, 4)), nrow=n, byrow=TRUE)
#' G = c(rep(1,n/2), rep(2,n/2))
#' x = mrs(X=X, G=G)
#' fit = summary(x, rho = 0.95, abs_eff = 1)
#' print(fit)
print.summary.mrs <-function(x, ...)
{
cat("------------------------\n")
cat("Posterior Null: ", x$Posterior_Null, "\n") cat("Prior Null : ", x$Prior_Null, "\n")
cat("------------------------\n\n")
if( x$Num_Regions>0) { cat("Top differential regions \n") cat("------------------------\n") for(i in 1:x$Num_Regions)
{
cat("PMAP: ", signif(x$Alt_Prob[i], digits=3), " |\t") cat("Effect Size: ", signif(x$Effect_Size[[i]], digits=3), " |\t")
cat("Region: ", signif(x$Regions[i,], digits=3), " |\t") cat("Direction: ", x$Directions[i], "\n")
cat("------------------------\n")
}
}

}

jacsor/MRS documentation built on May 18, 2019, 9:05 a.m.