博碩士論文 104225601 完整後設資料紀錄

DC 欄位 語言
DC.contributor統計研究所zh_TW
DC.creator何致晟zh_TW
DC.creatorZhisheng Heen_US
dc.date.accessioned2017-7-19T07:39:07Z
dc.date.available2017-7-19T07:39:07Z
dc.date.issued2017
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=104225601
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對設限存活資料(censored survival data)分析,Rodrigues等(2009)提出用Conway-Maxwell-Poisson (COM-Poisson)分佈為治愈模型(cure rate model)。對COM-Poisson治愈模型之特例——伯努利治愈模型(Bernoulli cure rate model),考慮使用不同之運算演算法,以最大概似估計法(maximum likelihood estimation)得參數之估計值。據Balakrishnan與Pal於2016以韋伯分佈(Weibull distribution)及於2015以廣義伽瑪分佈(generalized gamma distribution),假設為其壽命分佈(lifetime distribution)。進而導出之評分函數(score function)與黑塞矩陣(Hessian matrix),用以牛頓-拉弗森演算法(Newton-Raphson algorithm)及最大期望演算法(EM algorithm)。模擬為分析比較此二種演算法之表現。末了,實際資料分析作詳加闡明此方法模型。zh_TW
dc.description.abstractRodrigues et al. (2009) proposed the Conway-Maxwell-Poisson (COM-Poisson) distribution as a model for a cure rate in censored survival data. We consider computational algorithms for maximum likelihood estimation under the Bernoulli cure rate model, a special case of the COM-Poisson cure rate model. The Weibull distribution (Balakrishnan and Pal 2016) and the generalized gamma distribution (Balakrishnan and Pal 2015) are considered as lifetime distributions. We obtain all the expressions of the score function and Hessian matrix to perform the Newton-Raphson and EM algorithms. Simulations are conducted to compare the performance between the EM algorithm and Newton-Raphson algorithms. Finally, a real data is analyzed to illustrate the methods.en_US
DC.subject廣義伽瑪分佈zh_TW
DC.subject最大期望演算法zh_TW
DC.subject邏輯鏈接zh_TW
DC.subject牛頓-拉弗森演算法zh_TW
DC.subject存活分析zh_TW
DC.subject韋伯分佈zh_TW
DC.subjectGeneralized gamma distributionen_US
DC.subjectEM algorithmen_US
DC.subjectLogistic linken_US
DC.subjectNewton-Raphson algorithmen_US
DC.subjectSurvival analysisen_US
DC.subjectWeibull distributionen_US
DC.titleParametric likelihood inference with censored survival data under the COM-Poisson cure modelsen_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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