A modified Monte Carlo EM algorithm for a three-parameter distribution

Author

Ye, Zhen ; Xie, Meihua ; Shen, Yanming ; Tang, Loon Ching

Author_Institution

Dept. of Ind. & Syst. Eng., Nat. Univ. of Singapore, Singapore, Singapore

fYear

2011

fDate

14-17 Sept. 2011

Firstpage

172

Lastpage

176

Abstract

Statistical inference of a three-parameter distribution with closed-form mean residual life function is studied for complete and Type-II censored data. Because the log-likelihood function for this new distribution is not convex, the sequential quadratic programming method used for the maximum likelihood estimation easily diverges. Therefore, a modified Monte Carlo EM algorithm is proposed for parameter estimation. This modified algorithm is used to maintain the feasibility of the parameter vector during the evolutionary process, and is found to be robust in the sense that it is insensitive to the starting points.

Keywords

Monte Carlo methods; expectation-maximisation algorithm; inference mechanisms; quadratic programming; Monte Carlo EM algorithm; Type-II censored data; evolutionary process; log-likelihood function; maximum likelihood estimation; sequential quadratic programming method; statistical inference; three-parameter distribution; Approximation algorithms; Computational modeling; Equations; Inference algorithms; Markov processes; Maximum likelihood estimation; Monte Carlo methods; Markov Chain Monte Carlo; Maximum likelihood estimation; Progressively Type-II censoring; Weibull distribution;

fLanguage

English

Publisher

ieee

Conference_Titel

Quality and Reliability (ICQR), 2011 IEEE International Conference on

Conference_Location

Bangkok

Print_ISBN

978-1-4577-0626-4

Type

conf

DOI

10.1109/ICQR.2011.6031703

Filename

6031703