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Annals of Data Science
Erschienen in: Annals of Data Science 1/2019

01.02.2019

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

verfasst von: Manoj Kumar, Anurag Pathak, Sukriti Soni

Erschienen in: Annals of Data Science | Ausgabe 1/2019

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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.
Vorheriger Artikel NBA Game Result Prediction Using Feature Analysis and Machine Learning
Nächster Artikel Order Statistics from the Power Lindley Distribution and Associated Inference with Application

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Metadaten
Titel
Bayesian Inference for Rayleigh Distribution Under Step-Stress Partially Accelerated Test with Progressive Type-II Censoring with Binomial Removal
verfasst von
Manoj Kumar
Anurag Pathak
Sukriti Soni
Publikationsdatum
01.02.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Annals of Data Science / Ausgabe 1/2019
Print ISSN: 2198-5804
Elektronische ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-019-00192-w

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