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| 研究生： |
曹雅婷 Ya-ting Tsao |
|---|---|
| 論文名稱： |
個數資料之過離散性的強韌推論 Inference for overdispersion in count data without making distributional assumptions |
| 指導教授： |
鄒宗山
Tsung-shan Tsou |
| 口試委員: | |
| 學位類別： |
碩士 Master |
| 系所名稱： |
理學院 - 統計研究所 Graduate Institute of Statistics |
| 畢業學年度： | 99 |
| 語文別： | 中文 |
| 論文頁數： | 60 |
| 中文關鍵詞： | 過離散性的個數資料 、Bartlett第二等式 、對數迴歸模型 |
| 外文關鍵詞： | Bartlett''s second identity, over-dispersion count data, log regression model |
| 相關次數： | 點閱：6 下載：0 |
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本文之目的在於利用，當估計模型假設錯誤時，Bartlett的第二等式不正確的性質，來提出一個估計具有過離散性的個數資料之過離散係數的方法。再根據Presnell與Boos(2004)在附錄所提出的方法來估計過離散係數估計量的變異數，並探討估計方法的有效性。
論文中提出一個不需知道正確模型下估計過離散係數之方法，適用於對數迴歸模型或其他合理的迴歸模型。
This thesis provides a method for estimating the over-dispersion count data. And this method adopts the poisson distribution as the working model.
The violation of the Bartlett’s second identity is then made use of to give rise to a useful formula for the estimation of the over-dispersion. This new means is applicable for any sensible link function that relates the response probabilities to the variates.
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