rejectsampling: Rejecting sampling using a t proposal density

In LearnBayes: Functions for Learning Bayesian Inference

Description

Implements a rejection sampling algorithm for a probability density using a multivariate t proposal density

Usage

rejectsampling(logf,tpar,dmax,n,data)

Arguments

logf	function that defines the logarithm of the density of interest
tpar	list of parameters of t proposal density including the mean m, scale matrix var, and degrees of freedom df
dmax	logarithm of the rejection sampling constant
n	number of simulated draws from proposal density
data	data and or parameters used in the function logf

Value

matrix of simulated draws from density of interest

Author(s)

Jim Albert

Examples

data(cancermortality)
start=c(-7,6)
fit=laplace(betabinexch,start,cancermortality)
tpar=list(m=fit$mode,var=2*fit$var,df=4)
theta=rejectsampling(betabinexch,tpar,-569.2813,1000,cancermortality)

Example output

LearnBayes documentation built on May 1, 2019, 7:03 p.m.