Non-parametric estimation of the residual distribution

被引：136

作者：

Akritas, MG

Van Keilegom, I

机构：

[1] Limburgs Univ Ctr, Diepenbeek, Belgium

[2] Penn State Univ, University Pk, PA 16802 USA

来源：

SCANDINAVIAN JOURNAL OF STATISTICS | 2001年 / 28卷 / 03期

关键词：

asymptotic representation; goodness-of-fit; non-parametric regression residuals; prediction intervals; residual distribution; weak convergence;

D O I：

10.1111/1467-9469.00254

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：

Consider a heteroscedastic regression model Y = m(X) + sigma (X)epsilon, where the functions m and sigma are "smooth", and epsilon is independent of X. An estimator of the distribution of epsilon based on non-parametric regression residuals is proposed and its weak convergence is obtained. Applications to prediction intervals and goodness-of-fit tests are discussed.

引用

页码：549 / 567

页数：19

共 18 条

[1]

BUCKLEY MJ, 1988, BIOMETRIKA, V75, P189, DOI 10.1093/biomet/75.2.189

[2]

Devroye L. P, 1978, CAN J STAT, V6, P179

[3] WEAK CONVERGENCE OF SAMPLE DISTRIBUTION FUNCTION WHEN PARAMETERS ARE ESTIMATED [J].