mvImportanceSampling: Important Sampling for Multivariate variables

In pasudyan/ConstrMixMod: MCMC methods for flexible mixture modeling on constrained spaces

Description

This function evaluates integrals of a multivariate random variables using important sampling method with a multivariate Gaussian proposal

Usage

mvImportanceSampling(constr, mn, cv, muProp, sigProp, numObs)

Arguments

constr	a function that describes the domain or constraint of the observations
mn	mean of the observations to be generated
cv	covariance matrix of the observations to be generated
muProp	mean of the proposal distribution
sigProp	covariance matrix of the proposal distribution
numObs	number of observations to be generated

Value

value of integrals

Examples

genconst <- function(u1, u2, l1, l2) { in_set <- function(X) {
 if (nrow(X) == 1) X = t(X)
 X[1,] > l1 & X[1,] < u1 & X[2,] > l2 & X[2,] < u2 & X[3,] > l1 &
 X[3,] < u1 & X[4,] > l2 & X[4,] < u2 }}
constr  <- genconst(u = 0, u = 0, l1 = 1, l2 = 1)
mvImportanceSampling(constr, rep(1/2, 4), diag(0.1,4), rep(0,4), diag(0.3,4), 100)

pasudyan/ConstrMixMod documentation built on May 10, 2019, 8:26 a.m.