Bayesian Inference for Rayleigh Distribution Under Step-Stress Partially Accelerated Test with Progressive Type-II Censoring with Binomial Removal

Manoj Kumar (), Anurag Pathak and Sukriti Soni
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Manoj Kumar: Central University of Haryana
Anurag Pathak: Central University of Haryana
Sukriti Soni: Central University of Rajasthan

Annals of Data Science, 2019, vol. 6, issue 1, No 7, 117-152

Abstract: Abstract In this paper, we propose maximum likelihood estimators (MLEs) and Bayes estimators of parameters of the step-stress partially accelerated life testing of Rayleigh distribution in presence of progressive type-II censoring with binomial removal scheme under Square error loss function, General entropy loss function and Linear exponential loss function . The MLEs and corresponding Bayes estimators are compared in terms of their risks based on simulated samples from Rayleigh distribution. Also, we present to analyze two sets of real data to show its applicability.

Keywords: Step-stress partially accelerated test; MLEs; Bayes estimators; PT-II CBRs; SELF; GELF; LINEX (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s40745-019-00192-w

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