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Order restricted classical inference of a Weibull multiple step-stress model

Ayan Pal, Sharmishtha Mitra, Debasis Kundu

2020Journal of Applied Statistics17 citationsDOIOpen Access PDF

Abstract

In this paper, a multiple step-stress model is designed and analyzed when the data are Type-I censored. Lifetime distributions of the experimental units at each stress level are assumed to follow a two-parameter Weibull distribution. Further, distributions under each of the stress levels are connected through a tampered failure-rate based model. In a step-stress experiment, as the stress level increases, the load on the experimental units increases and hence the mean lifetime is expected to be shortened. Taking this into account, the aim of this paper is to develop the order restricted inference of the model parameters of a multiple step-stress model based on the frequentist approach. An extensive simulation study has been carried out and two real data sets have been analyzed for illustrative purposes.

Topics & Concepts

Weibull distributionFrequentist inferenceInferenceStress (linguistics)MathematicsStatisticsFailure rateApplied mathematicsStatistical inferenceComputer scienceBayesian inferenceBayesian probabilityArtificial intelligenceLinguisticsPhilosophyStatistical Distribution Estimation and ApplicationsProbabilistic and Robust Engineering DesignReliability and Maintenance Optimization
Order restricted classical inference of a Weibull multiple step-stress model | Litcius