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題 名 | Bayesian Estimation for Random Sample with One Vague Data=具有模糊資料的一組隨機樣本之貝氏估計法 |
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作 者 | 洪文良; 施登山; | 書刊名 | 華岡理科學報 |
卷 期 | 16 1999.05[民88.05] |
頁 次 | 頁97-106 |
分類號 | 319.5 |
關鍵詞 | 貝氏分析; 後驗分佈; 先驗分佈; 模糊資料; Bayesian analysis; Posterior distribution; Prior distribution; Vague data; |
語 文 | 英文(English) |
中文摘要 | 姚和黃(1996)兩位先生介紹了具有一個模糊資料的一組隨機樣本,並且以最大概似法估計未知參數θ。本文考慮參數θ的貝氏估計法,並且舉例說明貝氏估計法的優點。 |
英文摘要 | The idea of Bayesian analysis is that, since the posterior distribution supposedly contains all the available information about the parameter (both sample and prior information), any information about the parameter (both sample and prior information), any inference concerning the parameter should consist solely of features of this distribution. In this paper a general framework for Bayesian statistical inference is provided for the random sample with one vague data which was defined by Yao and Hwang. |
本系統中英文摘要資訊取自各篇刊載內容。