Varying coefficient transformation models with censored data
Varying coefficient transformation models with censored data
复制标题
使用删失数据改变系数变换模型
DOI：
10.1093/biomet/asq032
复制
发表时间：
2010-12-01
期刊：
影响因子：
2.7
通讯作者：
Tong, Xingwei
中科院分区：
文献类型：
--
作者：
Chen, Kani;Tong, Xingwei
针对变系数线性变换模型，提出了一种样条光滑的极大似然方法。估计和推断过程在计算上是容易的。在一定的正则性条件下，证明了估计量的相合性和渐近正态性。利用斯坦福大学移植数据进行的仿真研究表明，该方法在有限样本下表现良好，易于在实践中使用。版权所有2010年，牛津大学出版社。
A maximum likelihood method with spline smoothing is proposed for linear transformation models with varying coefficients. The estimation and inference procedures are computationally easy. Under some regularity conditions, the estimators are proved to be consistent and asymptotically normal. A simulation study using the Stanford transplant data is presented to show that the proposed method performs well with a finite sample and is easy to use in practice. Copyright 2010, Oxford University Press.