Exploring the application and formulation of the EM algorithm, The EM Algorithm and Related Statistical Models offers a valuable method to construct statistical models when only incomplete information is available, and proposes specific estimation algorithms for solutions to incomplete data problems. The text covers current topics including statistical models with latent variables, as well as neural network models, and Markov Chain Monte Carlo methods. It describes software resources valuable for the processing of the EM algorithm with incomplete data, for general analysis of latent structure models of categorical data, and for studies accelerated versions of the EM algorithm.