Optimal sample size allocation for accelerated life test under progressive type-II censoring with competing risks

ABSTRACT

In this article, we study the optimization problem of sample size allocation when the competing risks data are from a progressive type-II censoring in a constant-stress accelerated life test with multiple levels. The failure times of the individual causes are assumed to be statistically independent and exponentially distributed with different parameters. We obtain the estimates of the unknown parameters through a maximum likelihood method, and also derive the Fisher information matrix. We propose three optimization criteria and two search scenarios to obtain the sample size allocation at each stress level. Some numerical results are studied to illustrate the usage of the proposed methods.

KEYWORDS:

• A-optimality
• D-optimality
• expected test time
• exponential distribution
• Fisher information matrix
• variance-optimality

Acknowledgments

The authors wish to thank the Associate Editor and referee for valuable suggestions which led to the improvement of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work of this paper is partially supported by the National Science Council of ROC grant [NSC 102-2118-M-032-005-MY2] and the Ministry of Science and Technology of ROC grant [MOST 103-2811-M-032-010].