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  • 标题:Bayesian Inference on the Shape Parameter and Future Observation of Exponentiated Family of Distributions
  • 本地全文:下载
  • 作者:Sanku Dey ; Sudhansu S. Maiti
  • 期刊名称:Journal of Probability and Statistics
  • 印刷版ISSN:1687-952X
  • 电子版ISSN:1687-9538
  • 出版年度:2011
  • 卷号:2011
  • DOI:10.1155/2011/457472
  • 出版社:Hindawi Publishing Corporation
  • 摘要: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.
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