博碩士論文 962205024 完整後設資料紀錄

DC 欄位 語言
DC.contributor統計研究所zh_TW
DC.creator邱詩芸zh_TW
DC.creatorShih-yun Ciouen_US
dc.date.accessioned2009-6-19T07:39:07Z
dc.date.available2009-6-19T07:39:07Z
dc.date.issued2009
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=962205024
dc.contributor.department統計研究所zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract在各種領域中常會接觸到具有相關性的二分法資料,這些相關性可能來自於生物間的基因、環境、重複測量或是時間所造成。Royall and Tsou (2003)所提出的強韌概似函數方法,在大樣本下,使得二分法資料具有相關性或者資料並非來自二項分配時,皆能對迴歸參數做出正確的推導。 本文之目的在利用二項分配模型的修正項,得到估計群集內資料間相關性的新方法。 zh_TW
dc.description.abstractCorrelated data are commonly encountered in many fields. The correlation may come from the genetic heredity, familial aggregation, environmental heterogeneity, or repeated measures. Royall and Tsou (2003) proposed a parametric robust likelihood technique. With large samples, the adjusted binomial likelihood is asymptotically legitimate for correlated binary data. In this work, we use the adjustment by the binomial working model and obtain a new method for estimating the correlation between data in a cluster. en_US
DC.subject強韌概似函數zh_TW
DC.subject相關係數zh_TW
DC.subjectrobust likelihood functionen_US
DC.subjectcorrelationen_US
DC.title用強韌概似函數分析具相關性之二分法資料zh_TW
dc.language.isozh-TWzh-TW
DC.titleCorrelated binary data analysis using robust likelihooden_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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