ASYMPTOTIC NORMALITY OF A WEIGHTED INTEGRATED SQUARED ERROR OF KERNEL REGRESSION ESTIMATES WITH DATA-DEPENDENT BANDWIDTH

被引：5

作者：

LIERO, H ^{[1
]}

机构：

[1] KARL WEIERSTRASS INST MATH,O-1086 BERLIN,GERMANY

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 1992年 / 30卷 / 03期

关键词：

ADAPTIVE ESTIMATION; EMPIRICAL PROCESS; KERNEL ESTIMATOR; LIMIT THEOREM FOR THE ISE; NONPARAMETRIC REGRESSION;

D O I：

10.1016/0378-3758(92)90158-O

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Let (X, Y) be a bivariate random vector and let r(t) = E(Y\X = t) be the regression function of Y on X that has to be estimated from a sample of i.i.d. random vectors (X1, Y1),...,(X(n), Y(n)) having the same distribution as (X, Y). In the present paper it is shown that the normalized integrated squared error of a kernel estimator with data-driven bandwidth is asymptotically normally distributed.

引用

页码：307 / 325

页数：19

共 34 条

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