Estimation of Parameters of Generalized Inverted Exponential Distribution for Progressive Type-II Censored Sample with Binomial Removals

We obtained the maximum likelihood and Bayes estimators of the parameters of the generalized inverted exponential distribution in case of the progressive type-II censoring scheme with binomial removals. Bayesian estimation procedure has been discussed under the consideration of the square error and...

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Main Authors: Sanjay Kumar Singh, Umesh Singh, Manoj Kumar
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Journal of Probability and Statistics
Online Access:http://dx.doi.org/10.1155/2013/183652
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spelling doaj-220789786007420aad6b7ba474cf7e272020-11-24T23:58:36ZengHindawi LimitedJournal of Probability and Statistics1687-952X1687-95382013-01-01201310.1155/2013/183652183652Estimation of Parameters of Generalized Inverted Exponential Distribution for Progressive Type-II Censored Sample with Binomial RemovalsSanjay Kumar Singh0Umesh Singh1Manoj Kumar2Department of Statistics and DST-CIMS, Banaras Hindu University, Varanasi 221005, IndiaDepartment of Statistics and DST-CIMS, Banaras Hindu University, Varanasi 221005, IndiaDepartment of Statistics and DST-CIMS, Banaras Hindu University, Varanasi 221005, IndiaWe obtained the maximum likelihood and Bayes estimators of the parameters of the generalized inverted exponential distribution in case of the progressive type-II censoring scheme with binomial removals. Bayesian estimation procedure has been discussed under the consideration of the square error and general entropy loss functions while the model parameters follow the gamma prior distributions. The performances of the maximum likelihood and Bayes estimators are compared in terms of their risks through the simulation study. Further, we have also derived the expression of the expected experiment time to get a progressively censored sample with binomial removals, consisting of specified number of observations from generalized inverted exponential distribution. An illustrative example based on a real data set has also been given.http://dx.doi.org/10.1155/2013/183652
collection DOAJ
language English
format Article
sources DOAJ
author Sanjay Kumar Singh
Umesh Singh
Manoj Kumar
spellingShingle Sanjay Kumar Singh
Umesh Singh
Manoj Kumar
Estimation of Parameters of Generalized Inverted Exponential Distribution for Progressive Type-II Censored Sample with Binomial Removals
Journal of Probability and Statistics
author_facet Sanjay Kumar Singh
Umesh Singh
Manoj Kumar
author_sort Sanjay Kumar Singh
title Estimation of Parameters of Generalized Inverted Exponential Distribution for Progressive Type-II Censored Sample with Binomial Removals
title_short Estimation of Parameters of Generalized Inverted Exponential Distribution for Progressive Type-II Censored Sample with Binomial Removals
title_full Estimation of Parameters of Generalized Inverted Exponential Distribution for Progressive Type-II Censored Sample with Binomial Removals
title_fullStr Estimation of Parameters of Generalized Inverted Exponential Distribution for Progressive Type-II Censored Sample with Binomial Removals
title_full_unstemmed Estimation of Parameters of Generalized Inverted Exponential Distribution for Progressive Type-II Censored Sample with Binomial Removals
title_sort estimation of parameters of generalized inverted exponential distribution for progressive type-ii censored sample with binomial removals
publisher Hindawi Limited
series Journal of Probability and Statistics
issn 1687-952X
1687-9538
publishDate 2013-01-01
description We obtained the maximum likelihood and Bayes estimators of the parameters of the generalized inverted exponential distribution in case of the progressive type-II censoring scheme with binomial removals. Bayesian estimation procedure has been discussed under the consideration of the square error and general entropy loss functions while the model parameters follow the gamma prior distributions. The performances of the maximum likelihood and Bayes estimators are compared in terms of their risks through the simulation study. Further, we have also derived the expression of the expected experiment time to get a progressively censored sample with binomial removals, consisting of specified number of observations from generalized inverted exponential distribution. An illustrative example based on a real data set has also been given.
url http://dx.doi.org/10.1155/2013/183652
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AT umeshsingh estimationofparametersofgeneralizedinvertedexponentialdistributionforprogressivetypeiicensoredsamplewithbinomialremovals
AT manojkumar estimationofparametersofgeneralizedinvertedexponentialdistributionforprogressivetypeiicensoredsamplewithbinomialremovals
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