Nothing
#' Transforms ASReml-R gamma sampling variances to component scale
#'
#' The inverse of the Average Information matrix in an ASReml-R object produces
#' the sampling variances of the (co)variance components on the gamma scale.
#' This function scales these variances to the original component scale. This
#' allows for Confidence Intervals to be constructed about the variance
#' component estimates.
#'
#'
#' @param asr.object Object from a call to \code{asreml}
#' @return Returns a numeric vector of variances for each variance component in
#' an ASReml-R model.
#' @author \email{matthewwolak@@gmail.com}
#' @examples
#'
#' \dontrun{
#' library(asreml)
#' ginvA <- ainverse(warcolak)
#' ginvD <- makeD(warcolak[, 1:3])$listDinv
#' attr(ginvD, "rowNames") <- as.character(warcolak[, 1])
#' attr(ginvD, "INVERSE") <- TRUE
#' warcolak$IDD <- warcolak$ID
#' warcolak.mod <- asreml(trait1 ~ sex,
#' random = ~ vm(ID, ginvA) + vm(IDD, ginvD),
#' data = warcolak)
#' summary(warcolak.mod)$varcomp
#' sqrt(varTrans(warcolak.mod)) # sqrt() so can compare with standard errors from summary
#' }
#'
#' @export
varTrans <- function(asr.object){
if(asr.object$sigma2 == 1){
vars <- diag(aiFun(asr.object))
} else{
Rcomp <- which(asr.object$gammas == 1.00)
AI <- aiFun(asr.object)
comps <- asr.object$gammas * asr.object$sigma2
vars <- c(((asr.object$gammas[-Rcomp]^2) * diag(AI)[Rcomp] + comps[Rcomp]^2 * diag(AI)[-Rcomp] + 2*asr.object$gammas[-Rcomp]*comps[Rcomp]*AI[Rcomp, -Rcomp]), diag(AI)[Rcomp])
}
vars
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.