Maximum Likelihood Estimation of Tobit Factor Analysis for Multivariate t-Distribution

Abstract

We propose multivariate tobit factor analysis models by assuming multivariate t-distribution error in tobit factor analysis. To circumvent direct calculation of the intractable likelihood function, we apply the MCEM algorithm to obtain the MLEs with its E-step made feasible by Monte Carlo estimates and its M-step greatly simplified under Conditional Maximization. Standard errors are evaluated by using Louis's method. The algorithm was illustrated through a simulation study.

Keywords:

• EM algorithm
• Factor analysis
• Monte Carlo
• t-distribution
• Tobit model

Mathematics Subject Classification:

• 62H12
• 62H25

Acknowledgments

This work is partially supported by the Anhui Province College Excellent Young Talents Fund of China (No. 2009SQRZ176ZD), and the National Natural Science Foundation of China (No. 10971097, 10471135).