EM algorithm for Mixture Factor Analysis

This project is to explore the application of EM algorithms for maximum likelihood factor analysis. The first part is to evaluate the model fitting by comparing the precision and stability of the estimates by large numbers of simulations. The second part is to apply cross validation method to estimate the optimal number of groups from the data with underlining mixture factor structures. This project will explore and evaluate the cross validation method and assess its sensitivity.