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A consistent method of estimation for three-parameter generalized exponential distribution

Lookup NU author(s): Dr Kiran Prajapat

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Abstract

In this article, we provide a consistent method of estimation for the parameters of a three-parameter generalized exponential distribution which avoids the problem of unbounded likelihood function. The method is based on a maximum likelihood estimation of the shape parameter, which uses location and scale invariant statistic, originally proposed by Nagatsuka et al. (A consistent method of estimation for the three-parameter weibull distribution, Computational Statistics & Data Analysis 58:210–26). It has been shown that the estimators are unique and consistent for the entire range of the parameter space. We also present a Monte-Carlo simulation study along with the comparisons with some prominent estimation methods in terms of the bias and root mean square error. For the illustration purpose, the data analysis of a real lifetime data set has been reported.

Publication metadata

Author(s): Prajapat K, Mitra S, Kundu D

Publication type: Article

Publication status: Published

Journal: Communications in Statistics - Simulation and Computation

Year: 2021

Volume: 52

Issue: 6

Pages: 2471-2487

Online publication date: 19/04/2021

Acceptance date: 20/03/2021

ISSN (print): 0361-0918

ISSN (electronic): 1532-4141

Publisher: Taylor & Francis

URL: https://doi.org/10.1080/03610918.2021.1908557

DOI: 10.1080/03610918.2021.1908557

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