Asymptotic Normality for Regression Function Estimate Under Truncation and α-Mixing Conditions
Asymptotic Normality for Regression Function Estimate Under Truncation and α-Mixing Conditions
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DOI：
10.1080/03610921003666420
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发表时间：
2011-04
期刊：
影响因子：
--
通讯作者：
Han-Ying Liang
中科院分区：
文献类型：
--
作者：
Han-Ying Liang
In this article we establish pointwise asymptotic normality of nonparametric kernel estimator of regression function for a left truncation model. It is assumed that the lifetime observations with multivariate covariates form a stationary α-mixing sequence. Also, the asymptotic normality of the estimation of the covariable's density is considered. As a by-product, we obtain a uniform weak convergence rate for the product-limit estimator of the lifetime and truncated distributions under dependence, which is interesting independently. Finite sample behavior of the estimator of the regression function is investigated as well.
