This paper provides an extension of the work of Balakrishnan and Ling  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.
CitationBalakrishnan, 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.
- EM algorithm
- Inequality constrained least squares
- One-shot device
- Competing risks
- Masked data
- Exponential distribution
- ED01 Data