Abstract
In this article, we investigate the optimization problem when the competing risks data come from a progressive type II censoring in an accelerated life test with multiple levels of constant stress. The failure times of the individual causes are assumed to be independent and exponentially distributed with different parameters. We propose three criteria related to the Fisher's information matrix to determine the optimal stress level as well as the optimal sample allocation at each stress level. A real data set is studied to illustrate the application of the proposed criteria.
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