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Optimal step-stress testing for progressively Type-I censored data from exponential distribution
Authors:N Balakrishnan  Donghoon Han
Institution: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
Abstract:In this paper, a k  -step-stress accelerated life-testing is considered with an equal step duration ττ. 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 ττ is determined under this model. Next, we discuss the determination of optimal ττ 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., iτiτ, i=1,2,…,ki=1,2,,k). The determination of optimal ττ 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.
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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