gibbsNormal2: Gibbs sampler for a normal random sample with a conjugate...

In nclbayes: Functions, Demos and Examples of Bayesian Analysis and Basic MCMC

Description

Simulates realisations from the posterior distribution for the mean and precision in a normal distribution based on a random sample and a conjugate normal-gamma prior distribution by using a Gibbs sampler.

Usage

gibbsNormal2(N, initial, priorparam, n, xbar, s)

Arguments

N	length of MCMC chain.
initial	starting value for the algorithm.
priorparam	prior parameters b,c,g,h.
n	size of random sample.
xbar	mean of random sample.
s	standard deviation of random sample.

Examples

mcmcAnalysis(gibbsNormal2(N=100,initial=c(5.41,25),
 priorparam=c(5.41,0.25,2.5,0.1),n=23,xbar=5.4848,s=0.1882),rows=2)

nclbayes documentation built on May 2, 2019, 5:53 p.m.