Multinomial Data By KWANG WOO AHN and KUNG-SIK CHAN Department of Statistics and Actuarial Science, The University of Iowa, Iowa City, IA USA [email protected] [email protected] Summary We propose a new, block Gibbs sampling scheme for incomplete multinomial data. The new approach facilitates maximal blocking, thereby reducing serial dependency and speeding up the convergence of the ...

This paper gives precise, easy to compute bounds on the convergence time of the Gibbs sampler used in Bayesian image reconstruction. For sampling from the Gibbs distribution both with and without the presence of an external eld, bounds that are N 2 in the number of pixels are obtained, with a proportionality constant that is easy to calculate.