fcondXA: Conditional density evaluation in the semiparametric model

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

Conditional density evaluation in the semiparametric model

Description

This function evaluates a density path conditionally on a posterior realization of the normalized measure.

Usage

fcondXA(x, distr, Tau, J, sigma)

Details

For internal use.

Examples

## The function is currently defined as
function(x, distr = 1, Tau, J, sigma) {
  pJ <- J / sum(J)
  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)
  }
  fcondXA <- apply(K, 2, function(x) sum(x * pJ))
  return(fcondXA)
}

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