gs5cens2: Conditional posterior distribution of sigma in the case of...

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

Conditional posterior distribution of sigma in the case of censoring

Description

This function simulates from the conditional posterior distribution of sigma.

Usage

gs5cens2(
  sigma,
  xleft,
  xright,
  censor_code,
  y,
  distr = 1,
  asigma = 1,
  bsigma = 2,
  delta = 4
)

Details

For internal use

Examples

## The function is currently defined as
function(sigma, xleft, xright, censor_code, y, distr = 1, asigma = 1,
         bsigma = 2, delta = 4) {
  sigmaStar <- rgamma(1, shape = delta, rate = delta / sigma)
  sigmaT <- sigma
  qgammas <- sigmaT / sigmaStar
  Qgammas <- sigmaStar / sigmaT
  Term2 <- qgammas^(2 * delta - 1) * exp(-delta * (qgammas -
    Qgammas))
  Kgamma <- Qgammas^(asigma - 1) * exp(-bsigma * (sigmaStar -
    sigmaT))
  Prod <- 1
  for (i in seq_along(xleft)) {
    Prod <- Prod * dkcens2_1val(
      xleft = xleft[i], xright = xright[i],
      c_code = censor_code[i], distr = distr, mu = y[i],
      sigma = sigmaStar
    ) / dkcens2_1val(
      xleft = xleft[i],
      xright = xright[i], c_code = censor_code[i], distr = distr,
      mu = y[i], sigma = sigmaT
    )
  }
  q3 <- min(1, Kgamma * Prod * Term2)
  sigma <- ifelse(runif(1) <= q3, sigmaStar, sigmaT)
  return(sigma)
}

BNPdensity documentation built on April 1, 2023, 12:10 a.m.