EM algorithm for one-shot device testing with competing risks under exponential distribution

Narayanaswamy BALAKRISHNAN, Hon Yiu SO, Man Ho Alpha LING

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

This paper provides an extension of the work of Balakrishnan and Ling [1] by introducing a competing risks model into a one-shot device testing analysis under an accelerated life test setting. An Expectation Maximization (EM) algorithm is then developed for the estimation of the model parameters. An extensive Monte Carlo simulation study is carried out to assess the performance of the EM algorithm and then compare the obtained results with the initial estimates obtained by the Inequality Constrained Least Squares (ICLS) method of estimation. Finally, we apply the EM algorithm to a clinical data, ED01, to illustrate the method of inference developed here. Copyright © 2015 Elsevier Ltd.
Original languageEnglish
Pages (from-to)129-140
JournalReliability Engineering & System Safety
Volume137
Early online dateJan 2015
DOIs
Publication statusPublished - May 2015

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Testing
Monte Carlo simulation

Citation

Balakrishnan, N., So, H. Y., Ling, M. H. (2015). EM algorithm for one-shot device testing with competing risks under exponential distribution. Reliability Engineering & System Safety, 137, 129-140.

Keywords

  • EM algorithm
  • Inequality constrained least squares
  • One-shot device
  • Competing risks
  • Masked data
  • Exponential distribution
  • ED01 Data