The EM Algorithm for One-Shot Device Testing with Competing Risk Under Different Lifetimes Distributions

• Activity Number: 645
• Type: Topic Contributed
• Date/Time: Thursday, August 4, 2016 : 8:30 AM to 10:20 AM
• Sponsor: Quality and Productivity Section
• Author(s): Hon Yiu So* and Narayanaswamy Balakrishnan and Man Ho Ling
• Companies: McMaster University and McMaster University and Hong Kong Institute of Education
• Keywords: Expectation maximization ; One-shot device ; Competing risks ; Exponential distribution ; Weibull distribution ; Maximum likelihood estimation

Abstract

In this talk, we extend the recent works of Balakrishnan and Ling [1,2] by introducing a competing risk model into a one-shot device testing analysis under accelerated life test setting. Expectation maximization (EM) algorithms are developed for the estimation of model parameters under different lifetime distributions. Extensive Monte Carlo simulations are carried out to assess the performance of the proposed method of estimation. The advantages of the EM algorithms over the traditional Fisher scoring method are displayed through simulation.

[1] N. Balakrishnan, and M.H. Ling, ``EM algorithm for one-shot device testing under the exponential distribution,'' {\it Computational Statistics $\&$ Data Analysis,} vol. 56, pp. 502-509, 2012.

[2] N. Balakrishnan, and M.H. Ling, ``Expectation maximization algorithm for one shot device accelerated life testing with Weibull lifetimes, and variable parameters over stress,'' {\it IEEE Transactions on Reliability,} vol. 62, pp. 537-551, 2013.