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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/7744


    Title: 混合先驗分佈下誤差項為自我迴歸之線性混合效應模型的貝氏分析;Bayesian Inference on the Linear Mixed-Effect Models with Autoregressive Errors Using Mixture Priors
    Authors: 張逸塵;Yi-chen Zhang
    Contributors: 統計研究所
    Keywords: 自我迴歸模型;吉比氏抽樣法;混合先驗分佈;隨機效應;固定效應;貝氏預測;中位機率模型;Fixed effect;Random effect;Mixture prior;Gibbs sampling;AR(1) model;Median probability model;Bayesian prediction
    Date: 2009-06-10
    Issue Date: 2009-09-22 11:03:46 (UTC+8)
    Publisher: 國立中央大學圖書館
    Abstract: 本文主要目的在於探討誤差項具自我迴歸之貝氏線性混合效應模型。經由混合先驗分佈,找出顯著的固定效應與隨機效應變數,進而得到中位機率模型,並由該模型進行貝氏之推論與預測。最後將此模型應用在一組高血糖和相對高胰島素血症,對於葡萄糖的容忍度實驗之資料中,結果顯示,本文提出的方法可以提供準確的預測。 In this thesis, we address the problem of Bayesian linear mixed effects model with auto-regressive errors. We consider a mixture prior to identify subsets of covariates having nonzero fixed effect coefficients or nonzero random effects variance, and eventually obtain a median probability model, which is utilized for Bayesian inference and prediction. Finally, the proposed method is applied to a study of the association of hyperglycemia and relative hyperinsulinemia, and it yields very accurate prediction results.
    Appears in Collections:[Graduate Institute of Statistics] Electronic Thesis & Dissertation

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