R/p0.R

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

#' Centering function
#'
#' This function determines the centering density of the normalized random
#' measure.
#'
#' For internal use.
#'
#' @keywords internal
#' @examples
#'
#' ## The function is currently defined as
#' function(x, distr = NULL, mu = NULL, sigma = NULL) {
#'   if (is.null(distr)) {
#'     stop("Argument \"distr\" should be defined numeric with possible values 1,2, or 3")
#'   }
#'   else if (distr == 1) {
#'     a <- ifelse(is.null(mu), 0, mu)
#'     b <- ifelse(is.null(sigma), 1, sigma)
#'     p0 <- dnorm(x, mean = a, sd = b)
#'   }
#'   else if (distr == 2) {
#'     a <- ifelse(is.null(mu), 1, mu^2 / sigma^2)
#'     b <- ifelse(is.null(sigma), 1, mu / sigma^2)
#'     p0 <- dgamma(x, shape = a, rate = b)
#'   }
#'   else if (distr == 3) {
#'     a <- ifelse(is.null(mu), 0.5, (1 - mu) * (mu / sigma)^2 -
#'       mu)
#'     b <- ifelse(is.null(sigma), 1 / sqrt(12), (mu * (1 - mu) / sigma^2 -
#'       1) * (1 - mu))
#'     if (any(c(a, b) <= 0)) {
#'       stop(paste(
#'         "\nNegative Beta parameters:\n a =", a,
#'         ";\t b =", b
#'       ))
#'     }
#'     p0 <- dbeta(x, shape1 = a, shape2 = b)
#'   }
#'   else {
#'     stop("Argument \"distr\" should be defined numeric with possible values 1,2, or 3")
#'   }
#'   return(p0)
#' }
p0 <-
  function(x, distr = NULL, mu = NULL, sigma = NULL) {
    if (is.null(distr)) {
      stop("Argument \"distr\" should be defined numeric with possible values 1,2, or 3")
    }
    else if (distr == 1) {
      a <- ifelse(is.null(mu), 0, mu)
      b <- ifelse(is.null(sigma), 1, sigma)
      p0 <- dnorm(x, mean = a, sd = b)
    }
    else if (distr == 2) {
      a <- ifelse(is.null(mu), 1, mu^2 / sigma^2)
      b <- ifelse(is.null(sigma), 1, mu / sigma^2)
      p0 <- dgamma(x, shape = a, rate = b)
    }
    else if (distr == 3) {
      a <- ifelse(is.null(mu), 0.5, (1 - mu) * (mu / sigma)^2 -
        mu)
      b <- ifelse(is.null(sigma), 1 / sqrt(12), (mu * (1 - mu) / sigma^2 -
        1) * (1 - mu))
      if (any(c(a, b) <= 0)) {
        stop(paste(
          "\nNegative Beta parameters:\n a =", a,
          ";\t b =", b
        ))
      }
      p0 <- dbeta(x, shape1 = a, shape2 = b)
    }
    else {
      stop("Argument \"distr\" should be defined numeric with possible values 1,2, or 3")
    }
    return(p0)
  }