A COMPARISON OF VARIANCE ESTIMATORS IN NONPARAMETRIC REGRESSION

被引：0

作者：

CARTER, CK ^{[1
]}

EAGLESON, GK ^{[1
]}

机构：

[1] UNIV NEW S WALES,AUSTRALIAN GRAD SCH MANAGEMENT,POB 1,KENSINGTON,NSW 2033,AUSTRALIA

来源：

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL | 1992年 / 54卷 / 03期

关键词：

SMOOTHING; SPLINES; VARIANCE;

D O I：

暂无

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：

We compare two estimators of error variance, both based on quadratic forms in the residuals about smoothing spline fits to data. The estimators are compared over the whole range of values of the smoothing parameter as well as for data-based choices of the smoothing parameter. We show that the commonly used estimator of variance has the serious drawback of underestimating the error variance for small choices of the smoothing parameter. This drawback is not shared by a simple, but more computationally intensive, alternative.

引用

页码：773 / 780

页数：8

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