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ISSN: 1549-3644 (Print)
ISSN: 1558-6359 (Online)
Research Article Open Access

Estimation for Unknown Parameters of the Burr Type-XII Distribution Based on an Adaptive Progressive Type-II Censoring Scheme

Montaser M. Amein1
  • 1 Al-Azhar University, Egypt

Abstract

In this study, the Maximum Likelihood Estimation (MLE) and Bayes estimation are exploited to make interval estimation based on adaptive progressive Type-II censoring for the Burr Type-XII distribution. Explicit form for the parameters of Bayes estimator doesn’t exist, so, Markov Chain Monte Carlo (MCMC) method is used as approximation to find posterior mean under squared error loss function. Real data set are presented to illustrate the methods of inference.

Journal of Mathematics and Statistics
Volume 12 No. 2, 2016, 119-126

DOI: https://doi.org/10.3844/jmssp.2016.119.126

Submitted On: 16 February 2016 Published On: 29 April 2016

How to Cite: Amein, M. M. (2016). Estimation for Unknown Parameters of the Burr Type-XII Distribution Based on an Adaptive Progressive Type-II Censoring Scheme. Journal of Mathematics and Statistics, 12(2), 119-126. https://doi.org/10.3844/jmssp.2016.119.126

Open AccessCopyright: © 2016 Montaser M. Amein. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • An Adaptive Type-II Progressive Censoring Scheme
  • Bayesian and Non-Bayesian Estimations
  • Gibbs and Metropolis Sampler
  • Burr Type-XII Distribution