EFFICIENT ESTIMATION FOR AN ACCELERATED FAILURE TIME MODEL WITH A CURE FRACTION.
EFFICIENT ESTIMATION FOR AN ACCELERATED FAILURE TIME MODEL WITH A CURE FRACTION.
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作者：
Wenbin Lu
研究了具有治愈率的加速失效时间模型的基于核的非参数极大似然估计。一个EM算法被开发来计算回归参数和未知误差密度的估计，其中核平滑的条件轮廓似然在M步中被最大化。我们证明了，通过适当地选择核带宽参数，得到的估计是一致的和渐近正态的。渐近协方差矩阵可以通过使用EM算法反演从轮廓似然获得的经验Fisher信息矩阵来一致地估计。数值例子被用来说明所提出的估计的有限样本性能。
We study the accelerated failure time model with a cure fraction via kernel-based nonparametric maximum likelihood estimation. An EM algorithm is developed to calculate the estimates for both the regression parameters and the unknown error density, in which a kernel-smoothed conditional profile likelihood is maximized in the M-step. We show that with a proper choice of the kernel bandwidth parameter, the resulting estimates are consistent and asymptotically normal. The asymptotic covariance matrix can be consistently estimated by inverting the empirical Fisher information matrix obtained from the profile likelihood using the EM algorithm. Numerical examples are used to illustrate the finite-sample performance of the proposed estimates.