rbiNormGibbs: Illustrate Bivariate Normal Gibbs Sampler

In bayesm: Bayesian Inference for Marketing/Micro-Econometrics

Illustrate Bivariate Normal Gibbs Sampler

Description

rbiNormGibbs implements a Gibbs Sampler for the bivariate normal distribution. Intermediate moves are plotted and the output is contrasted with the iid sampler. This function is designed for illustrative/teaching purposes.

Usage

rbiNormGibbs(initx=2, inity=-2, rho, burnin=100, R=500)

Arguments

initx	initial value of parameter on x axis (def: 2)
inity	initial value of parameter on y axis (def: -2)
rho	correlation for bivariate normals
burnin	burn-in number of draws (def: 100)
R	number of MCMC draws (def: 500)

Details

(\theta_1, \theta_2) ~ N( (0,0), \Sigma) with \Sigma = matrix(c(1,rho,rho,1),ncol=2)

Value

R x 2 matrix of draws

Author(s)

Peter Rossi, Anderson School, UCLA, [e-mail].

References

For further discussion, see Chapters 2 and 3, Bayesian Statistics and Marketing by Rossi, Allenby, and McCulloch.

Examples

## Not run: out=rbiNormGibbs(rho=0.95)

bayesm documentation built on Sept. 24, 2023, 1:07 a.m.