ess {FastGP}

Sampling from a Bayesian model with a multivariate normal prior distribution

Description

This function uses elliptical slice sampling to sample from a Bayesian model in which the prior is multivariate normal (JMLR Murray, Adams, and MacKay 2010)

Usage

ess(log.lik,Y, Sig, N_mcmc,burn_in,N,flag)

Arguments

log.lik

Log-lik function in model which is assumed to take two arguments: the first contains the parameters/latent variables and the second the observed data Y

Y

Observed data.

Sig

Covariance matrix associated with the prior distribution on the parameters/latent variable vector.

N_mcmc

Number of desired mcmc samples.

burn_in

Number of burn-in iterations.

N

Dimensionality of parameter/latent variable vector.

flag

Set to TRUE for MASS implementation of mvrnorm (which may be more stable but slow), FALSE for FastGP implementation of rcpp_rmvnorm (which is faster but less stable)

Author(s)

Giri Gopalan [e-mail]

Examples

# See demo/FastGPdemo.r.