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Journal of Data Science


Adaptive Type-II Progressive Censoring Schemes based on Maximum Product Spacing with Application of Generalized Rayleigh Distribution
Volume 17, Issue 4 (2019), pp. 802–831
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access
Published
4 August 2022

Abstract

In this paper, parameters estimation for the generalized Rayleigh (GR) distribution are discussed under the adaptive type-II progressive censoring schemes based on maximum product spacing. A comparison studies with another methods as maximum likelihood, and Bayesian estimation by use Markov chain Monte Carlo (MCMC) are discussed. Also, reliability estimation and hazard function are obtained. A numerical study using real data and Monte Carlo Simulation are performed to compare between different methods.

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Keywords
Generalized Rayleigh distribution Adaptive Type-II progressive censoring Maximum Product Spacing, Bayesian estimation and Reliability estimation

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