博碩士論文 100225014 完整後設資料紀錄

DC 欄位 語言
DC.contributor統計研究所zh_TW
DC.creator高帆萱zh_TW
DC.creatorFan-Hsuan Kaoen_US
dc.date.accessioned2013-6-25T07:39:07Z
dc.date.available2013-6-25T07:39:07Z
dc.date.issued2013
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=100225014
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在處理競爭風險的資料時,由於造成特定物件失效的原因有許多種,因此估計特定失效物件的具體-理由分布函數是相當重要的。然而,在面對多維的失效時間時,即使是二維資料其亦具有相當難度。本篇論文中,我們考慮Sankaran 等人在 (2006) 所提出的一種無母數的二維具體-理由分布函數估計量。在此,我們提出一個改善原有方法的一種新的無母數估計量。我們以理論上以及數值上去展示我們的估計量較原有的估計量有更小的均方誤差。我們亦證明此估計量的一致性。針對此估計量的表現我們將進行模擬研究。最後我們把此有效的方法利用到老鼠與蠑螈的資料上並以3D圖來表現其效果。zh_TW
dc.description.abstractFor competing risks data, it is important to estimate the cause-specific distribution function of a particular failure event, which is the failure probability in the presence of other risks. However, if multiple failure events per subject are available, estimation procedures become challenging, even for the bivariate case. In this thesis, we consider the nonparametric estimation of bivariate cause-specific distribution function which is discussed in Sankaran et al. (2006). In particular, we propose a new nonparametric estimator which improves upon the estimator of Sankaran et al. It is shown theoretically and numerically that the proposed estimator has smaller mean square error than the existing one. The consistency of the proposed estimator is also established. A simulation study is conducted to investigate the performance of the proposed estimator. The usefulness of the method is illustrated by the salamander data and mouse data.en_US
DC.subject二維存活函數zh_TW
DC.subject無母數估計量zh_TW
DC.subject競爭風險zh_TW
DC.subject具體-理由分布函數zh_TW
DC.subject右設限zh_TW
DC.subjectBivariate survival functionen_US
DC.subjectNonparametric estimationen_US
DC.subjectCompeting risken_US
DC.subjectCause-specific distribution functionen_US
DC.subjectRight censoringen_US
DC.titleAn improved nonparametric estimator of distribution function for bivariate competing risks modelen_US
dc.language.isoen_USen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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