Bayesian Inference on the Shape Parameter and Future Observation of Exponentiated Family of Distributions

Bayesian Inference on the Shape Parameter and Future Observation of Exponentiated Family of Distributions

The Bayes estimators of the shape parameter of exponentiated family of distributions have been derived by considering extension of Jeffreys' noninformative as well as conjugate priors under different scale-invariant loss functions, namely, weighted quadratic loss function, squared-log error los...

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Main Authors: Sanku Dey, Sudhansu S. Maiti
Format: Article
Language:English
Published: Hindawi Limited 2011-01-01
Series:Journal of Probability and Statistics
Online Access:http://dx.doi.org/10.1155/2011/457472
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spelling doaj-16429f5e682547bd9723943719a37adb2020-11-24T21:35:52ZengHindawi LimitedJournal of Probability and Statistics1687-952X1687-95382011-01-01201110.1155/2011/457472457472Bayesian Inference on the Shape Parameter and Future Observation of Exponentiated Family of DistributionsSanku Dey0Sudhansu S. Maiti1Department of Statistics, St. Anthony's College, Shillong 793 001, IndiaDepartment of Statistics, Visva-Bharati University, Santiniketan 731 235, IndiaThe Bayes estimators of the shape parameter of exponentiated family of distributions have been derived by considering extension of Jeffreys' noninformative as well as conjugate priors under different scale-invariant loss functions, namely, weighted quadratic loss function, squared-log error loss function and general entropy loss function. The risk functions of these estimators have been studied. We have also considered the highest posterior density (HPD) intervals for the parameter and the equal-tail and HPD prediction intervals for future observation. Finally, we analyze one data set for illustration.http://dx.doi.org/10.1155/2011/457472
collection DOAJ
language English
format Article
sources DOAJ
author Sanku Dey
Sudhansu S. Maiti
spellingShingle Sanku Dey
Sudhansu S. Maiti
Bayesian Inference on the Shape Parameter and Future Observation of Exponentiated Family of Distributions
Journal of Probability and Statistics
author_facet Sanku Dey
Sudhansu S. Maiti
author_sort Sanku Dey
title Bayesian Inference on the Shape Parameter and Future Observation of Exponentiated Family of Distributions
title_short Bayesian Inference on the Shape Parameter and Future Observation of Exponentiated Family of Distributions
title_full Bayesian Inference on the Shape Parameter and Future Observation of Exponentiated Family of Distributions
title_fullStr Bayesian Inference on the Shape Parameter and Future Observation of Exponentiated Family of Distributions
title_full_unstemmed Bayesian Inference on the Shape Parameter and Future Observation of Exponentiated Family of Distributions
title_sort bayesian inference on the shape parameter and future observation of exponentiated family of distributions
publisher Hindawi Limited
series Journal of Probability and Statistics
issn 1687-952X
1687-9538
publishDate 2011-01-01
description The Bayes estimators of the shape parameter of exponentiated family of distributions have been derived by considering extension of Jeffreys' noninformative as well as conjugate priors under different scale-invariant loss functions, namely, weighted quadratic loss function, squared-log error loss function and general entropy loss function. The risk functions of these estimators have been studied. We have also considered the highest posterior density (HPD) intervals for the parameter and the equal-tail and HPD prediction intervals for future observation. Finally, we analyze one data set for illustration.
url http://dx.doi.org/10.1155/2011/457472
work_keys_str_mv AT sankudey bayesianinferenceontheshapeparameterandfutureobservationofexponentiatedfamilyofdistributions
AT sudhansusmaiti bayesianinferenceontheshapeparameterandfutureobservationofexponentiatedfamilyofdistributions
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