| DC 欄位 |
值 |
語言 |
| DC.contributor | 統計研究所 | zh_TW |
| DC.creator | 曹雅婷 | zh_TW |
| DC.creator | Ya-ting Tsao | en_US |
| dc.date.accessioned | 2011-7-8T07:39:07Z | |
| dc.date.available | 2011-7-8T07:39:07Z | |
| dc.date.issued | 2011 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=982205018 | |
| dc.contributor.department | 統計研究所 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 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。
| zh_TW |
| dc.description.abstract | 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.
| en_US |
| DC.subject | 過離散性的個數資料 | zh_TW |
| DC.subject | Bartlett第二等式 | zh_TW |
| DC.subject | 對數迴歸模型 | zh_TW |
| DC.subject | Bartlett's second identity | en_US |
| DC.subject | over-dispersion count data | en_US |
| DC.subject | log regression model | en_US |
| DC.title | 個數資料之過離散性的強韌推論 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Inference for overdispersion in count data without making distributional assumptions | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |