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Statistical Inference for Pareto Distribution based on Progressive Type-I Hybrid Censoring Scheme

by M. M. Mohie El-Din, A. R. Shafay, M. Nagy, A. Gamal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 4
Year of Publication: 2017
Authors: M. M. Mohie El-Din, A. R. Shafay, M. Nagy, A. Gamal
10.5120/ijca2017915802

M. M. Mohie El-Din, A. R. Shafay, M. Nagy, A. Gamal . Statistical Inference for Pareto Distribution based on Progressive Type-I Hybrid Censoring Scheme. International Journal of Computer Applications. 178, 4 ( Nov 2017), 1-8. DOI=10.5120/ijca2017915802

@article{ 10.5120/ijca2017915802,
author = { M. M. Mohie El-Din, A. R. Shafay, M. Nagy, A. Gamal },
title = { Statistical Inference for Pareto Distribution based on Progressive Type-I Hybrid Censoring Scheme },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2017 },
volume = { 178 },
number = { 4 },
month = { Nov },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number4/28659-2017915802/ },
doi = { 10.5120/ijca2017915802 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:49:27.379758+05:30
%A M. M. Mohie El-Din
%A A. R. Shafay
%A M. Nagy
%A A. Gamal
%T Statistical Inference for Pareto Distribution based on Progressive Type-I Hybrid Censoring Scheme
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 4
%P 1-8
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, the maximum likelihood and Bayesian estimations are developed based on progressive Type-I hybrid censored sample from the Pareto distribution. The Bayesian estimators for the unknown parameters are computed using the squared error loss function. Also, the point and interval Bayesian predictions for the unobserved failures from the same sample and that from the future sample are derived. Moreover, a Monte Carlo simulation study is carried out to compare the performance of the maximum likelihood and the Bayesian estimators. Finally, numerical example is presented for illustrating all the inferential procedures developed here.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Bayesian estimation Bayesian prediction Pareto distribution Maximum likelihood estimation progressive hybrid censoring sample

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