STATISTICAL INFERENCES UNDER MODIFIED WEIBULL DISTRIBUTION BASED ON PROGRESSIVE FIRST-FAILURE CENSORING SCHEME

Saieed F. Ateya; Elham A. Madhagi

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STATISTICAL INFERENCES UNDER MODIFIED WEIBULL DISTRIBUTION BASED ON PROGRESSIVE FIRST-FAILURE CENSORING SCHEME

Author(s)

Saieed F. Ateya Mathematics & Statistics Department, Taif University,Hawia, Taif, Saudi Arabia.; Mathematics Department, Faculty of Science,Assiut University, Egypt

Elham A. Madhagi Department of Statistics, College of Science, Qassim University,Qassim,Saudi Arabia; Mathematics Department, Faculty of Education, Hodeidah University,Hodeidah,Yemen

Abstract

In this paper, point and interval estimations under modified Weibull (MW ) distribution have been studied based on progressive first-failure censored scheme. The Bayes estimates ( BE' ) have been computed based on squared error (ES ) and (Linex) loss functions and using Markov Chain Monte Carlo (MCMC ) algorithm. Also, based on this censoring scheme, the interval estimation problem of the parameters of distribution have been studied. A Monte Carlo simulation study has been carried out to compare the performances of the different methods by computing the mean squared errors (MSE's ). Finally, point and interval estimates for all parameters have been studied based on a real data set as an illustrative example.

Publication Details

Page(s) 103-116

DOI DOI not available

Published Journal: Pakistan Journal of Statistics, Volume: 36, Issue: 2, Year: 2020

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Keywords

Markov Chain Monte Carlo method., Modified Weibull distribution, Progressive first-failure censoring

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