BGSIMD-package: Efficient Block Gibbs Sampler with Data from an Incomplete...

In BGSIMD: Block Gibbs Sampler with Incomplete Multinomial Distribution

Description

Implement an efficient block Gibbs sampler for Bayesian analysis with incomplete data from a multinomial distribution taking values from the k categories 1,2,...,k, where data are assumed to miss at random and each missing datum belongs to one and only one of m distinct non-empty proper subsets A1, A2,..., Am of 1,2,...,k and the k categories are labelled such that only consecutive A's may overlap.

Details

Package:	BGSIMD
Type:	Package
Version:	1.0
Date:	2009-02-06
License:	GPL (>= 2)
LazyLoad:	yes

Author(s)

Kwang Woo Ahn <[e-mail]> and Kung-Sik Chan <[e-mail]>

References

Ahn, K. W. and Chan, K. S. (2007) Efficient Markov chain Monte Carlo with incomplete multinomial data, Technical report 382, The University of Iowa

BGSIMD documentation built on May 2, 2019, 5:12 a.m.