Maximum likelihood estimation of multinomial probit factor analysis models for multivariate t-distribution

Authors:
Jie Jiang;Xinsheng Liu;Keming Yu
Affiliations:
State Key Laboratory of Mechanics and Control of Mechanical Structures, Institute of Nano Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China 210016 and College of Science, ...;State Key Laboratory of Mechanics and Control of Mechanical Structures, Institute of Nano Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China 210016 and College of Science, ...;Department of Mathematical Sciences, Brunel University, Uxbridge, UK UB8 3PH and Business School, Shihezi University, Shihezi, China 832003
Venue:
Computational Statistics
Year:
2013

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Abstract

We propose a model for multinomial probit factor analysis by assuming t-distribution error in probit factor analysis. To obtain maximum likelihood estimation, we use the Monte Carlo expectation maximization algorithm with its M-step greatly simplified under conditional maximization and its E-step made feasible by Monte Carlo simulation. Standard errors are calculated by using Louis's method. The methodology is illustrated with numerical simulations.