淡江大學機構典藏:Item 987654321/58762
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    题名: Nonparametric maximum likelihood estimator in a semiparametric mixture model for competing risks data
    作者: 溫啟仲;Chang, I-SHOU;Hsiung, CHAO A.;Wu, YUH-JENN;Yang, CHE-CHI
    贡献者: 淡江大學數學學系
    日期: 2007-12-01
    上传时间: 2011-10-01 21:09:20 (UTC+8)
    摘要: This paper describes our studies on non-parametric maximum-likelihood estimators in a semiparametric mixture model for competing-risks data, in which proportional hazards models are specified for failure time models conditional on cause and a multinomial model is specified for the marginal distribution of cause conditional on covariates. We provide a verifiable identifiability condition and, based on it, establish an asymptotic profile likelihood theory for this model. We also provide efficient algorithms for the computation of the non-parametric maximum-likelihood estimate and its asymptotic variance. The success of this method is demonstrated in simulation studies and in the analysis of Taiwan severe acute respiratory syndrome data.
    關聯: Scandinavian Journal of Statistics 34(4), pp.870-895
    DOI: 10.1111/j.1467-9469.2007.00567.x
    显示于类别:[數學學系暨研究所] 期刊論文

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