Bayesian inference and optimal plan for the family of inverted exponentiated distribution under doubly censored data

淡江大學機構典藏 > 商管學院 > 統計學系暨研究所 > 期刊論文 > Item 987654321/126932

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题名:	Bayesian inference and optimal plan for the family of inverted exponentiated distribution under doubly censored data
作者:	Gupta, Chandan Kumar;Chandra, Prakash;Tripathi, Yogesh Mani;Wu, Shuo-jye
关键词:	Bayes estimate;Bayesian prediction;double censoring;inverted exponentiated exponential distribution;maximum likelihood estimate
日期:	2025-02-28
上传时间:	2025-03-20 09:31:27 (UTC+8)
摘要:	In this paper, we consider inference upon unknown parameters of the family of inverted exponentiated distributions when it is known that data are doubly censored. Maximum likelihood and Bayes estimates under different loss functions are derived for estimating the parameters. We use Metropolis-Hastings algorithm to draw Markov chain Monte Carlo samples, which are used to compute the Bayes estimates and construct the Bayesian credible intervals. Further, we present point and interval predictions of the censored data using the Bayesian approach. The performance of proposed methods of estimation and prediction are investigated using simulation studies, and two illustrative examples are discussed in support of the suggested methods. Finally, we propose the optimal plans under double censoring scheme.
關聯:	Hacettepe Journal of Mathematics and Statistics 54(1), pp. 237-262
DOI:	10.15672/hujms.1373691
显示于类别:	[統計學系暨研究所] 期刊論文

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