Efficient Markov chain Monte Carlo with incomplete multinomial data
- First Online:
- Cite this article as:
- Ahn, K.W. & Chan, KS. Stat Comput (2010) 20: 447. doi:10.1007/s11222-009-9136-9
- 105 Downloads
We propose a block Gibbs sampling scheme for incomplete multinomial data. We show that the new approach facilitates maximal blocking, thereby reducing serial dependency and speeding up the convergence of the Gibbs sampler. We compare the efficiency of the new method with the standard, non-block Gibbs sampler via a number of numerical examples.