Non-parametric estimation of the residual distribution

被引：131
|
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.
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页码：549 / 567
页数：19
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