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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/4941

    Title: 無母數隨機邊界模型之貝氏分析
    Other Titles: Bayesian Inference of the Nonparametric Stochastic Frontier Models
    Authors: 黃河泉
    Contributors: 淡江大學財務金融學系
    Date: 2005
    Issue Date: 2009-03-16 11:27:30 (UTC+8)
    Abstract: 隨機邊界模型通常被用來衡量一廠商的無效率程度。然而,我們常常發現其對於邊界的函數設定情形非常敏感。所以,即使是誤差分配的設定是正確的,錯誤的「技術」(邊界) 設定將導致錯誤的「無效率」推論。本篇文章因此放寬傳統的「參數」隨機邊界模型而考慮一個「無母數」的隨機邊界模型來避免設定誤差。我們利用貝氏方法中的馬可夫鍊蒙地卡羅方法來估計、分析與推論模型相關係數,而且估計之結果俱有小樣本性質。我們也推導出其所需之完全條件分配,並預期以一實際資料來應用與展現其實用性。
    Appears in Collections:[財務金融學系暨研究所] 研究報告

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