#' @title Binormal model AUC function
#'
#' @description {Returns the Binormal model ROC-AUC corresponding to
#' specified parameters. See also \code{\link{UtilAnalyticalAucsRSM}}, \code{\link{UtilAucPROPROC}}
#' and \code{\link{UtilAucCBM}}}
#'
#' @param a The \code{a} parameter of the binormal model (separation of
#' non-diseased and diseased pdfs)
#' @param b The \code{b} parameter of the binormal model (std. dev. of
#' non-diseased diseased pdf; diseased pdf has unit std. dev)
#'
#'
#' @return Binormal model-predicted ROC-AUC
#'
#' @examples
#' a <- 2;b <- 0.7
#' UtilAucBIN(a,b)
#'
#' @references
#' Dorfman DD, Alf E (1969) Maximum-Likelihood Estimation of Parameters of Signal-Detection Theory and
#' Determination of Confidence Intervals - Rating-Method Data, Journal of Mathematical Psychology. 6:487-496.
#'
#'
#' @importFrom stats pnorm
#'
#' @export
#'
UtilAucBIN <- function (a, b){
auc <- pnorm(a/sqrt(1+b^2))
return (auc)
}
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