Bayesian and Non-Bayesian Inference for Survival Data Using Generalised Exponential Distribution

A two-parameter lifetime distribution was introduced by Kundu and Gupta known as generalised exponential distribution. This distribution has been touted to be an alternative to the well-known 2-parameter Weibull and gamma distributions. We seek to determine the parameters and the survival function o...

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Main Authors: Chris Bambey Guure, Samuel Bosomprah
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Journal of Probability and Statistics
Online Access:http://dx.doi.org/10.1155/2013/364705
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author Chris Bambey Guure
Samuel Bosomprah
author_facet Chris Bambey Guure
Samuel Bosomprah
author_sort Chris Bambey Guure
collection DOAJ
description A two-parameter lifetime distribution was introduced by Kundu and Gupta known as generalised exponential distribution. This distribution has been touted to be an alternative to the well-known 2-parameter Weibull and gamma distributions. We seek to determine the parameters and the survival function of this distribution. The survival function determines the probability that a unit under investigation will survive beyond a certain specified time, say, (). We have employed different data sets to estimate the parameters and see how well the distribution can be used to analyse survival data. A comparison is made about the estimators used in this study. Standard errors of the estimators are determined and used for the comparisons. A simulation study is also carried out, and the mean squared errors and absolute bias are obtained for the purpose of comparison.
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spelling doaj-art-f2f0209f9c484439b1e703695f19ac9a2025-02-03T01:08:50ZengWileyJournal of Probability and Statistics1687-952X1687-95382013-01-01201310.1155/2013/364705364705Bayesian and Non-Bayesian Inference for Survival Data Using Generalised Exponential DistributionChris Bambey Guure0Samuel Bosomprah1Department of Biostatistics, School of Public Health, University of Ghana, Legon Accra, GhanaDepartment of Biostatistics, School of Public Health, University of Ghana, Legon Accra, GhanaA two-parameter lifetime distribution was introduced by Kundu and Gupta known as generalised exponential distribution. This distribution has been touted to be an alternative to the well-known 2-parameter Weibull and gamma distributions. We seek to determine the parameters and the survival function of this distribution. The survival function determines the probability that a unit under investigation will survive beyond a certain specified time, say, (). We have employed different data sets to estimate the parameters and see how well the distribution can be used to analyse survival data. A comparison is made about the estimators used in this study. Standard errors of the estimators are determined and used for the comparisons. A simulation study is also carried out, and the mean squared errors and absolute bias are obtained for the purpose of comparison.http://dx.doi.org/10.1155/2013/364705
spellingShingle Chris Bambey Guure
Samuel Bosomprah
Bayesian and Non-Bayesian Inference for Survival Data Using Generalised Exponential Distribution
Journal of Probability and Statistics
title Bayesian and Non-Bayesian Inference for Survival Data Using Generalised Exponential Distribution
title_full Bayesian and Non-Bayesian Inference for Survival Data Using Generalised Exponential Distribution
title_fullStr Bayesian and Non-Bayesian Inference for Survival Data Using Generalised Exponential Distribution
title_full_unstemmed Bayesian and Non-Bayesian Inference for Survival Data Using Generalised Exponential Distribution
title_short Bayesian and Non-Bayesian Inference for Survival Data Using Generalised Exponential Distribution
title_sort bayesian and non bayesian inference for survival data using generalised exponential distribution
url http://dx.doi.org/10.1155/2013/364705
work_keys_str_mv AT chrisbambeyguure bayesianandnonbayesianinferenceforsurvivaldatausinggeneralisedexponentialdistribution
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