Watanabe M., Yamaguchi K. (eds.) The EM Algorithm and Related Statistical Models

N.-Y.: CRC Press, 2003. - 250p.Exploring the application and formulation of the EM algorithm, The EM Algorithm and Related Statistical Models offers a valuable method for constructing 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 and for general analysis of latent structure models of categorical data, and studies accelerated versions of the EM algorithm.Incomplete Data and the Generation Mechanisms
Incomplete Data and the EM Algorithm
Statistical Models and the EM Algorithm
Robust Model and the EM Algorithm
Latent Structure Model and the EM Algorithm
Extensions of the EM Algorithm
Convergence Speed and Acceleration of the EM Algorithm
EM Algorithm in Neural Network Learning
Markov Chain Monte Carlo
Appendix A: SOLASTM 3.0 for Missing Data Analysis
Appendix B: l EM