Nothing
compute.threshold.YI.AROC.bnp <-
function(object, newdata, ci.level = 0.95, parallel = c("no", "multicore", "snow"), ncpus = 1, cl = NULL) {
doMCMCTH <- function(k, res0, L, yd, Xd, Xhp, p) {
nd <- length(yd)
np <- length(p)
npred <- nrow(Xhp)
if(L == 1) {
up <- 1 - pnorm(yd, mean = Xd%*%res0$beta[k,], sd = res0$sd[k])
} else {
up <- 1 - apply(t(res0$probs[k,]*t(pnorm(yd, mean = tcrossprod(Xd, res0$beta[k,,]), sd = rep(res0$sd[k,], each = length(yd))))), 1, sum)
}
aux <- rexp(nd, 1)
weights <- aux/sum(aux)
AROC <- apply(weights*outer(up, p, "<="), 2, sum)
dif <- AROC - p
FPF.s <- mean(p[which(dif == max(dif))])
YI.s <- max(dif)
thresholds <- vector(length = npred)
if(L > 1){
mu.h <- Xhp%*%t(res0$beta[k,,])
for(i in 1:npred) {
aux0 <- norMix(mu = c(mu.h[i,]), sigma = res0$sd[k,], w = res0$probs[k,])
thresholds[i] <- qnorMix(1 - FPF.s, aux0)
}
}
if(L == 1){
mu.h <- Xhp%*%res0$beta[k,]
#for(i in 1:npred) {
# thresholds[i] <- qnorm(1 - FPF.s, mu.h[i], Sigma0[k])
#}
thresholds <- qnorm(1 - FPF.s, mu.h, res0$sd[k])
}
res <- list()
res$FPF.s <- FPF.s
res$YI.s <- YI.s
res$thresholds <- thresholds
res
}
if(class(object)[1] != "AROC.bnp") {
stop(paste0("This function cannot be used for this object class: ", class(object)[1]))
}
parallel <- match.arg(parallel)
#names.cov <- all.vars(object$fit$formula)[-1]
names.cov <- get_vars_formula(object$fit$formula)
if(!missing(newdata) && !inherits(newdata, "data.frame"))
stop("Newdata must be a data frame")
if(!missing(newdata) && length(names.cov) != 0 && sum(is.na(match(names.cov, names(newdata)))))
stop("Not all needed variables are supplied in newdata")
if(missing(newdata)) {
newdata <- cROCData(object$data, names.cov, object$group)
} else {
newdata <- as.data.frame(newdata)
newdata <- na.omit(newdata[,names.cov,drop = FALSE])
}
p <- seq(0, 1, length = 500)
X0p <- predict(object$fit$mm, newdata = newdata)$X
if(object$mcmc$nsave > 0) {
do_mc <- do_snow <- FALSE
if (parallel != "no" && ncpus > 1L) {
if (parallel == "multicore") {
do_mc <- .Platform$OS.type != "windows"
} else if (parallel == "snow") {
do_snow <- TRUE
}
if (!do_mc && !do_snow) {
ncpus <- 1L
}
loadNamespace("parallel") # get this out of the way before recording seed
}
# Seed
#if (!exists(".Random.seed", envir = .GlobalEnv, inherits = FALSE)) runif(1)
#seed <- get(".Random.seed", envir = .GlobalEnv, inherits = FALSE)
# Apply function
resBoot <- if (ncpus > 1L && (do_mc || do_snow)) {
if (do_mc) {
parallel::mclapply(seq_len(object$mcmc$nsave), doMCMCTH, res0 = object$fit, L = object$prior$L, yd = object$data_model$y$d, Xd = object$data_model$X$d, Xhp = X0p, p = p, mc.cores = ncpus)
} else if (do_snow) {
if (is.null(cl)) {
cl <- parallel::makePSOCKcluster(rep("localhost", ncpus))
if(RNGkind()[1L] == "L'Ecuyer-CMRG") {
parallel::clusterSetRNGStream(cl)
}
res <- parallel::parLapply(cl, seq_len(object$mcmc$nsave), doMCMCTH, res0 = object$fit, L = object$prior$L, yd = object$data_model$y$d, Xd = object$data_model$X$d, Xhp = X0p, p = p)
parallel::stopCluster(cl)
res
} else {
if(!inherits(cl, "cluster")) {
stop("Class of object 'cl' is not correct")
} else {
parallel::parLapply(cl, seq_len(object$mcmc$nsave), doMCMCTH, res0 = object$fit, L = object$prior$L, yd = object$data_model$y$d, Xd = object$data_model$X$d, Xhp = X0p, p = p)
}
}
}
} else {
lapply(seq_len(object$mcmc$nsave), doMCMCTH, res0 = object$fit, L = object$prior$L, yd = object$data_model$y$d, Xd = object$data_model$X$d, Xhp = X0p, p = p)
}
resBoot <- simplify2array(resBoot)
FPF.s <- simplify2array(resBoot["FPF.s",])
YI.s <- simplify2array(resBoot["YI.s",])
thresholds <- simplify2array(resBoot["thresholds",])
} else {
stop("nsave should be larger than zero.")
}
alpha <- (1-ci.level)/2
YI <- c(mean(YI.s), quantile(YI.s, c(alpha, 1-alpha)))
FPF <- c(mean(FPF.s), quantile(FPF.s, c(alpha, 1-alpha)))
names(YI) <- names(FPF) <- c("est","ql", "qh")
res <- list()
res$call <- match.call()
res$newdata <- newdata
res$thresholds <- cbind(est = apply(thresholds, 1, mean), ql = apply(thresholds, 1, quantile, alpha), qh = apply(thresholds, 1, quantile, 1-alpha))
res$YI <- YI
res$FPF <- FPF
res
}
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