Composition Algorithms For Conditional Distributions

This chapter is about two recently published algorithms that can be used to sample from conditional distributions. We show how the efficiency of the algorithms can be improved when a sample is required from many conditional distributions. Using real-data examples from educational measurement, we show how the algorithms can be used to sample from intractable full-conditional distributions of the person and item parameters in an application of the Gibbs sampler.