國家衛生研究院 NHRI:Item 3990099045/1767
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    题名: An asymptotic theory for the nonparametric maximum likelihood estimator in the Cox gene model
    作者: Chang, IS;Hsuing, CA;Wang, MC;Wen, CC
    贡献者: Division of Biostatistics and Bioinformatics;National Institute of Cancer Research
    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.
    关键词: Statistics & Probability
    日期: 2005-10
    關聯: Bernoulli. 2005 Oct;11(5):863-892.
    Link to: http://dx.doi.org/10.3150/bj/1130077598
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1350-7265&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000232729100006
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=33845699610
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