Fractional principal components regression: a general approach to biased estimators
作者:
Wonwoo Lee,
Jeffrey B. Birch,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 1988)
卷期:
Volume 17,
issue 3
页码: 713-727
ISSN:0361-0918
年代: 1988
DOI:10.1080/03610918808812689
出版商: Marcel Dekker, Inc.
关键词: multicollinearity;ridge regression;simulation
数据来源: Taylor
摘要:
Several biased estimators have been proposed as alternatives to the least squares estimator when multicollinearity is present in the multiple linear regression model. The ridge estimator and the principal components estimator are two techniques that have been proposed for such problems. In this paper the class of fractional principal component estimators is developed for the multiple linear regression model. This class contains many of the biased estimators commonly used to combat multicollinearity. In the fractional principal components framework, two new estimation techniques are introduced. The theoretical performances of the new estimators are evaluated and their small sample properties are compared via simulation with the ridge, generalized ridge and principal components estimators
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