Research Article | OPEN ACCESS
On Random Censored Exponential Distribution
Chris Bambey Guure
Institute for Mathematical Research, University Putra Malaysia, 43400, Serdang, Selangor, Malaysia
Bolgatanga Senior High School, Mail Box 176, Bolgatanga, Ghana
Research Journal of Applied Sciences, Engineering and Technology 2013 21:5022-5025
Received: September 06, 2012 | Accepted: October 05, 2012 | Published: May 20, 2013
Abstract
The Exponential distribution has attracted the attention of statisticians working on theory and methods as well as in various fields of lifetime data analysis. In this study, we employ gamma non-informative prior and generalised (data-dependent) non-informative prior proposed by Guure and Ibrahim (2012) using squared error loss function. The Bayesian estimate of the scale parameter of the Exponential distribution is obtained by making use of Lindley’s approximation procedure and compared with the classical maximum likelihood estimator. Mean Squared Error (MSE) and the absolute bias of the estimators are determined via simulation study for the purpose of comparison. It has been observed from the simulation study that, Bayes estimator with the generalised non- informative prior outperformed the gamma non-informative prior and the classical maximum likelihood estimator.
Keywords:
Bayesian, exponential distribution, gamma and generalised non-informative priors, random censoring, simulation study,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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