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Estimating a parameter of Burr type XII distribution using hybrid censored observations

Manoj Kumar Rastogi (Department of Mathematics, Indian Institute of Technology Patna, Patna, India)
Yogesh Mani Tripathi (Department of Mathematics, Indian Institute of Technology Patna, Patna, India)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Article publication date: 6 September 2011

Abstract

Purpose

Burr distribution has been proved to be a useful failure model. It can assume different shapes which allow it to be a good fit for various lifetimes data. Hybrid censoring is an important way of generating lifetimes data. The purpose of this paper is to estimate an unknown parameter of the Burr type XII distribution when data are hybrid censored.

Design/methodology/approach

The problem is dealt with through both the classical and Bayesian point of view. Specifically, the methods of estimation used to tackle the problem are maximum likelihood estimation method and Bayesian method. Empirical Bayesian approach is also considered. The performance of all estimates is compared through their mean square error values. The paper employs Monte Carlo simulation to evaluate the mean square error values of all estimates.

Findings

The key findings of the paper are that the Bayesian estimates are superior to the maximum likelihood estimates (MLE).

Practical implications

This work has practical importance. Indeed, the proposed methods are applied to real life data.

Originality/value

The paper is original and is quite applicable in lifetimes data analysis.

Keywords

Citation

Rastogi, M.K. and Mani Tripathi, Y. (2011), "Estimating a parameter of Burr type XII distribution using hybrid censored observations", International Journal of Quality & Reliability Management, Vol. 28 No. 8, pp. 885-893. https://doi.org/10.1108/02656711111162532

Publisher

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Emerald Group Publishing Limited

Copyright © 2011, Emerald Group Publishing Limited