Optimal step-stress testing for progressively Type-I censored data from exponential distribution |
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Authors: | N. Balakrishnan Donghoon Han |
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Affiliation: | 1. Department of Mathematics and Statistics, McMaster University, Hamilton, Ont., Canada L8S 4K1;2. Department of Statistics, University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2 |
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Abstract: | In this paper, a k -step-stress accelerated life-testing is considered with an equal step duration τ. For small to moderate sample sizes, a practical modification is made to the model previously considered by Gouno et al. [2004. Optimal step-stress test under progressive Type-I censoring. IEEE Trans. Reliability 53, 383–393] in order to guarantee a feasible k -step-stress test under progressive Type-I censoring, and the optimal τ is determined under this model. Next, we discuss the determination of optimal τ under the condition that the step-stress test proceeds to the k -th stress level, and the efficiency of this conditional inference is compared to that of the previous case. In all cases considered, censoring is allowed at each point of stress change (viz., iτ, i=1,2,…,k). The determination of optimal τ is discussed under C-optimality, D-optimality, and A-optimality criteria. We investigate in detail the case of progressively Type-I right censored data from an exponential distribution with a single stress variable. |
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Keywords: | Accelerated life-testing A-optimality Change-point Conditional inference Cumulative exposure model C-optimality D-optimality Fisher information Maximum likelihood estimation Order statistics Progressive Type-I censoring |
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