期刊論文
| 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 | en |
| ISSN | 0361-0918 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
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| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/41190 ) |