normgibbs {smfsb} | R Documentation |
This function runs a simple Gibbs sampler for the Bayesian posterior distribution of the mean and precision given a normal random sample.
normgibbs(N, n, a, b, cc, d, xbar, ssquared)
N |
The number of iterations of the Gibbs sampler. |
n |
The sample size of the normal random sample. |
a |
The shape parameter of the gamma prior on the sample precision. |
b |
The scale parameter of the gamma prior on the sample precision. |
cc |
The mean of the normal prior on the sample mean. |
d |
The precision of the normal prior on the sample mean. |
xbar |
The sample mean of the data. eg. |
ssquared |
The sample variance of the data. eg. |
An R matrix object containing the samples of the Gibbs sampler.
postmat=normgibbs(N=1100,n=15,a=3,b=11,cc=10,d=1/100,xbar=25,ssquared=20) postmat=postmat[101:1100,] op=par(mfrow=c(3,3)) plot(postmat) plot(postmat,type="l") plot.new() plot(ts(postmat[,1])) plot(ts(postmat[,2])) plot(ts(sqrt(1/postmat[,2]))) hist(postmat[,1],30) hist(postmat[,2],30) hist(sqrt(1/postmat[,2]),30) par(op)