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#' Conditional posterior distribution of the latents Y
#'
#' This function simulates form the conditional posterior distribution of the
#' latents Y.
#'
#' For internal use.
#'
#' @keywords internal
#' @examples
#'
#' ## The function is currently defined as
#' function(x, distr = 1, Tau, J, sigma) {
#' K <- matrix(NA, nrow = length(Tau), ncol = length(x))
#' for (i in seq(Tau)) {
#' K[i, ] <- dk(x, distr = distr, mu = Tau[i], sigma = sigma) *
#' J[i]
#' }
#' pK <- prop.table(K, margin = 2)
#' y <- apply(pK, 2, function(x) sample(Tau, size = 1, prob = x))
#' return(y)
#' }
fcondYXA <-
function(x, distr, Tau, J, sigma) {
K <- matrix(NA, nrow = length(Tau), ncol = length(x))
for (i in seq(Tau)) {
K[i, ] <- dk(x, distr = distr, mu = Tau[i], sigma = sigma) *
J[i]
}
pK <- prop.table(K, margin = 2)
y <- apply(pK, 2, function(x) sample(Tau, size = 1, prob = x))
return(y)
}
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