ML Fitting of Mixture Models
Geoffrey John McLachlan, David Alan Peel · Wiley series in probability and statistics · 2000
This chapter contains sections titled: Introduction ML Estimation Information Matrices Asymptotic Covariance Matrix of MLE Properties of MLEs for Mixture Models Choice of Root Test for a Consistent Root Application of EM Algorithm for Mixture Models Fitting Mixtures of Mixtures Maximum a Posteriori Estimation An Aitken Acceleration-Based Stopping Criterion Starting Values for EM Algorithm Stochastic EM Algorithm Rate of Convergence of the EM Algorithm Information Matrix for Mixture Models Provision of Standard Errors Speeding up Convergence Outlier Detection from a Mixture Partial Classification Partial Nonrandom Classification Classification ML Approach