BGSIMD-package {BGSIMD}R Documentation

Efficient Block Gibbs Sampler with Data from an Incomplete Multinomial Distribution


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.


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


Kwang Woo Ahn <> and Kung-Sik Chan <>


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

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