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Partially linear transformation models with varying coefficients for multivariate failure time data

机译:用于多元故障时间数据的具有变化系数的部分线性变换模型

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This paper studies the estimation and inference of Varying coefficients and parameters in the partially linear transformation models for multivariate failure time data. A profile martingale-based estimating method that includes global and local estimating equations is proposed. Asymptotic properties of the estimators are established. Some numerical simulations are given to show the performance of the estimation method in finite-sample situation. In order to reduce the computational burden, a simple and useful one-step estimator method is used. We further suggest a delete-a-group jackknife method to estimate asymptotic variance of estimators. A real data set from the Busselton Population Health Surveys is analyzed to illustrate the proposed methods. (C) 2015 Elsevier Inc. All rights reserved.
机译:本文研究了多元失效时间数据的部分线性变换模型中变量系数和参数的估计和推断。提出了一种基于轮廓mar的估计方法,该方法包括全局和局部估计方程。建立估计量的渐近性质。数值模拟表明了该方法在有限样本情况下的性能。为了减轻计算负担,使用了一种简单且有用的单步估计器方法。我们进一步建议使用删除一组折刀方法来估计估计量的渐近方差。对来自巴瑟尔顿人口健康调查的真实数据集进行了分析,以说明所提出的方法。 (C)2015 Elsevier Inc.保留所有权利。

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