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dc.contributor.author花文妤en_US
dc.contributor.authorWen-Yu Huaen_US
dc.contributor.author王維菁en_US
dc.contributor.authorWeijing Wangen_US
dc.date.accessioned2014-12-12T03:07:19Z-
dc.date.available2014-12-12T03:07:19Z-
dc.date.issued2006en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT009426518en_US
dc.identifier.urihttp://hdl.handle.net/11536/81459-
dc.description.abstract本論文主要是考慮在Copula模式之下,雙變元存活資料受限於右設限之半母數推論.目前存在許多估計相關性參數之半母數推論方法.我們比較三種推論方法針對不存在解釋變數之同質性資料.並利用迴歸的概念將現有的方法延伸至處理邊際異質的資料.最後,藉由模擬結果檢視上述方法之有限樣本的表現.zh_TW
dc.description.abstractThe thesis considers semi-parametric inference based on Copula models for bivariate survival data subject to right censoring. There exist several semi-parametric inference approaches to estimating the association parameter. We examine and compare three approaches developed for homogeneous data in absence of covariates. Then we extend these methods to a regression setting that accounts for marginal heterogeneity explained by the covariates. Finite-sample performances are examined by simulations.en_US
dc.language.isoen_USen_US
dc.subject雙變元存活資料zh_TW
dc.subjectCox 比例風險模式zh_TW
dc.subject相關存活時間zh_TW
dc.subjectClayton模式zh_TW
dc.subjectCopula模式zh_TW
dc.subject半母數推論zh_TW
dc.subject二階段估計式zh_TW
dc.subject2 2 表格zh_TW
dc.subjectBivariate survival data;en_US
dc.subjectCox proportional hazard modelen_US
dc.subjectCorrelated failure timesen_US
dc.subjectClayton modelen_US
dc.subjectCopula modelen_US
dc.subjectSemi-parametric inferenceen_US
dc.subjectTwo-stage estimationen_US
dc.subjectTwo-by-two tables.en_US
dc.titleCopula模式之下 雙變元存活資料之統計推論zh_TW
dc.titleStatistical Inference for Bivariate Survival Data Based onen_US
dc.typeThesisen_US
dc.contributor.department統計學研究所zh_TW
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