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    題名: An asymptotic theory for the nonparametric maximum likelihood estimator in the Cox gene model
    作者: I-Shou Chang
    Chao Agnes Hsiung
    Mei-Chuan Wang
    Chi-Chung Wen
    王美娟
    溫啓仲
    貢獻者: 臺北市立教育大學數學資訊教育學系
    關鍵詞: age at onset
    asymptotic normality
    Cox gene model
    discrete frailty model
    identifiability
    nonparametric maximum likelihood estimate
    profile likelihood information
    日期: 2005
    上傳時間: 2009-08-04 09:57:16 (UTC+8)
    摘要: The Cox model with a gene effect for age at onset was introduced and studied by Li, Thompson and Wijsman. We study the nonparametric maximum likelihood estimation of the gene effect and the regression coefficient in this model. We indicate conditions under which the parameters are identifiable and the nonparametric maximum likelihood estimate is consistent and asymptotically normal. We also apply the theory of observed profile information to obtain a consistent estimate of the asymptotic variance. Besides providing theoretical support for Li et al., our work provides an alternative approach to the numerical methods in this model.
    關聯: Bernoulli, V11(5) , p.863-892.
    顯示於類別:[數學系(含數學教育碩士班)] 期刊論文

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