教師資料查詢 | 類別: 期刊論文 | 教師: 林千代 Lin Chien-tai (瀏覽個人網頁)

標題:Monte Carlo Methods for Bayesian Inference on the Linear Hazard Rate Distribution
學年95
學期1
出版(發表)日期2006/09/01
作品名稱Monte Carlo Methods for Bayesian Inference on the Linear Hazard Rate Distribution
作品名稱(其他語言)
著者林千代; Lin, Chien-tai; Wu, Sam J. S.; Balakrishnan, N.
單位淡江大學數學學系
出版者Taylor & Francis
著錄名稱、卷期、頁數Communications in Statistics: Simulation and Computation 35(3), pp.575-590
摘要The Bayesian estimation and prediction problems for the linear hazard rate distribution under general progressively Type-II censored samples are considered in this article. The conventional Bayesian framework as well as the Markov Chain Monte Carlo (MCMC) method to generate the Bayesian conditional probabilities of interest are discussed. Sensitivity of the prior for the model is also examined. The flood data on Fox River, Wisconsin, from 1918 to 1950, are used to illustrate all the methods of inference discussed in this article.
關鍵字Bayesian computation; General progressive Type-II censoring; Markov Chain Monte Carlo (MCMC) method; Prediction; Simulation
語言英文
ISSN0361-0918
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收錄於SCI
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