博碩士論文 91245002 完整後設資料紀錄

DC 欄位	值	語言
DC.contributor	統計研究所	zh_TW
DC.creator	陳建宏	zh_TW
DC.creator	Chien-Hung Chen	en_US
dc.date.accessioned	2007-7-12T07:39:07Z
dc.date.available	2007-7-12T07:39:07Z
dc.date.issued	2007
dc.identifier.uri	http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=91245002
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	本論文中，先介紹由 Royall 與 Tsou 在2003年所提出的強韌概似函數的觀念。利用這個方法，首先建立了對於二變數資料的相關係數在廣義線性模型架構下的迴歸參數的強韌概似比檢定。其次，對於具有相關性的個數資料的平均數，建立一個強韌分數檢定。最後，對於上述具有相關性的個數資料的平均數在廣義線性模型架構下，對於迴歸參數建立一個強韌概似比檢定。 這些概似函數並不需要知道資料的真正分配，只要四階或二階動差存在即可。這些強韌方法的效率，經由模擬與真實資料呈現。	zh_TW
dc.description.abstract	In this thesis, we introduce the robust likelihood function proposed by Royall and Tsou (2003). Based on the method we first establish a robust parametric likelihood ratio test about regression parameters for the correlation coefficients modeled in a generalized linear model fashion. Next, we construct a robust parametric score test to compare means of several dependent populations of count. Furthermore, a robust parametric likelihood ratio test for regression parameters of means for correlated count data is proposed. The validity of the proposed likelihoods requires no knowledge of the true underlying distributions, so long as they have finite fourth or second moments. The efficacy of the robust methodology is demonstrated via simulations and real examples.	en_US
DC.subject	二維常態	zh_TW
DC.subject	強韌概似比檢定	zh_TW
DC.subject	多變數負二項模型	zh_TW
DC.subject	廣義線性模型	zh_TW
DC.subject	強韌分數檢定	zh_TW
DC.subject	Multivariate negative binomial	en_US
DC.subject	Bivariate normal	en_US
DC.title	相關性資料的有母數強韌推論	zh_TW
dc.language.iso	zh-TW	zh-TW
DC.title	Parametric Robust Inferences for Correlated Data	en_US
DC.type	博碩士論文	zh_TW
DC.type	thesis	en_US
DC.publisher	National Central University	en_US