R/rfystarcens2.R

In BNPdensity: Ferguson-Klass Type Algorithm for Posterior Normalized Random Measures

#' Conditional posterior distribution of the distinct Ystar in the case of
#' censoring
#'
#' This function evaluates the ratio of conditional posterior distributions of
#' the distinct latents Ystar.
#'
#' For internal use
#'
#' @keywords internal
#' @examples
#'
#' ## The function is currently defined as
#' function(v, v2, xleft, xright, censor_code, distr.k, sigma.k,
#'          distr.p0, mu.p0, sigma.p0) {
#'   alpha <- p0(v, distr = distr.p0, mu = mu.p0, sigma = sigma.p0) / p0(v2,
#'     distr = distr.p0, mu = mu.p0, sigma = sigma.p0
#'   )
#'   Prod <- 1
#'   for (i in seq_along(xleft)) {
#'     fac <- dkcens2_1val(
#'       xleft = xleft[i], xright = xright[i],
#'       c_code = censor_code[i], distr = distr.k, mu = v,
#'       sigma = sigma.k
#'     ) / dkcens2_1val(
#'       xleft = xleft[i], xright = xright[i],
#'       c_code = censor_code[i], distr = distr.k, mu = v2,
#'       sigma = sigma.k
#'     )
#'     Prod <- Prod * fac
#'   }
#'   f <- alpha * Prod
#'   return(f)
#' }
rfystarcens2 <-
  function(v, v2, xleft, xright, censor_code, distr.k, sigma.k,
           distr.p0, mu.p0, sigma.p0) {
    alpha <- p0(v, distr = distr.p0, mu = mu.p0, sigma = sigma.p0) / p0(v2,
      distr = distr.p0, mu = mu.p0, sigma = sigma.p0
    )
    Prod <- 1
    for (i in seq_along(xleft)) {
      fac <- dkcens2_1val(
        xleft = xleft[i], xright = xright[i],
        c_code = censor_code[i], distr = distr.k, mu = v,
        sigma = sigma.k
      ) / dkcens2_1val(
        xleft = xleft[i], xright = xright[i],
        c_code = censor_code[i], distr = distr.k, mu = v2,
        sigma = sigma.k
      )
      Prod <- Prod * fac
    }
    f <- alpha * Prod
    return(f)
  }