A generalized view on continuum regression

被引：27

作者：

Björkström, A ^{[1
]}

Sundberg, R ^{[1
]}

机构：

[1] Univ Stockholm, S-10691 Stockholm, Sweden

来源：

SCANDINAVIAN JOURNAL OF STATISTICS | 1999年 / 26卷 / 01期

关键词：

cross-validation; linear prediction; near collinearity; partial least squares regression (PLS); principal component regression (PCR); ridge regression; shrinkage;

D O I：

10.1111/1467-9469.00134

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 generalize the relationship between continuum regression (Stone & Brooks, 1990) and ridge regression, by showing that any optimization principle will yield a regressor proportional to a ridge regressor, provided only that the principle implies maximizing a function of the regressor's sample correlation coefficient and its sample variance, This relationship shows that continuum regression as defined via ridge regression ("least squares ridge regression") is a more generally valid methodology than previously realized, and also opens up for alternative choices of its second and subsequent factors.

引用

页码：17 / 30

页数：14

共 14 条

[1]

Bjorkstrom A, 1996, J ROY STAT SOC B MET, V58, P703

[2]

Brown P. J., 1993, MEASUREMENT REGRESSI

[3] PLS SHRINKS [J].