Conditional Inference for the Weibull Extension Model Based on the Generalized Order Statistics

M. Maswadah; A. A. EL-Faheem

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Conditional Inference for the Weibull Extension Model Based on the Generalized Order Statistics

Author(s)

M. Maswadah Department of Mathematics, Faculty of Science, Aswan University, Egypt

A. A. EL-Faheem Department of Mathematics, Faculty of Science, Aswan University, Egypt

Abstract

In recent years, a new class of models has been proposed to exhibit the bathtub-shaped failure rate functions. The Weibull extension model is one of these models, which is asymptotically related to the ordinary Weibull model and is capable of modeling the bathtub-shaped and increasing failure rate lifetime data. This paper presents the conditional inference for constructing the confidence intervals for the Weibull extension parameters based on the generalized order statistics. For measuring the performances of this approach comparing to the Asymptotic maximum likelihood estimates, Simulation studies have been carried out, that indicated the conditional intervals possess a good statistical properties and they can perform quite well even when the sample size is extremly small. An illustrative examples based on real data are given to illustrate the confidence intervals developed in this paper.

Publication Details

Page(s) 199-214

DOI DOI not available

Published Journal: Pakistan Journal of Statistics and Operation Research, Volume: 14, Issue: 2, Year: 2018

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Keywords

Weibull distribution, Progressive type-II censored samples with binomial random removals, Weibull extension model, Modified Weibull model, Generalized Pareto model, Lamox distribution, Asymptotic maximum likelihood estimates, Burr-type XII distribution

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