| DC 欄位 |
值 |
語言 |
| DC.contributor | 統計研究所 | zh_TW |
| DC.creator | 陳昱廷 | zh_TW |
| DC.creator | Yu-ting Chen | en_US |
| dc.date.accessioned | 2015-7-29T07:39:07Z | |
| dc.date.available | 2015-7-29T07:39:07Z | |
| dc.date.issued | 2015 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=102225003 | |
| 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 | 在配適相關性資料時，關聯結構（Copula）模型是一種目前常用的方法。本文探討在廣義線性模型的假設下，當關聯結構模型假設錯誤時，迴歸參數之估計量的一致性問題。同時我們也將二元負二項模型的結果與關聯結構模型結果做對比。 | zh_TW |
| dc.description.abstract | Copula models are popular in modeling correlated data. This research investigates the performance of Copula models when model assumption fails. In the setting of generalized linear models we will show that regression parameter estimates are sensitive to model misspecification and provide an alternative approach to inference about regression parameters without knowing the true underlying distribution. | en_US |
| DC.subject | 關聯結構模型 | zh_TW |
| DC.subject | 強韌概似函數 | zh_TW |
| DC.subject | 二元負二項分配 | zh_TW |
| DC.subject | Copula model | en_US |
| DC.subject | robust likelihood function | en_US |
| DC.subject | bivariate negative binomial | en_US |
| DC.title | 二維計數關聯結構模型推論之強韌性的探討 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |