Joint Continuum Regression for Multiple Predictands
作者:
Rodney Brooks,
Mervyn Stone,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1994)
卷期:
Volume 89,
issue 428
页码: 1374-1377
ISSN:0162-1459
年代: 1994
DOI:10.1080/01621459.1994.10476876
出版商: Taylor & Francis Group
关键词: Cross-validation;Moore-Penrose inverse;Multivariate predictand;Partial least squares;Principal components
数据来源: Taylor
摘要:
This article generalizes continuum regression (CR) in the hope that regressors “jointly constructed” for several predictands might improve on the separate prediction of individual predictands. The generalization developed is a mixture of principal components regression and de Jong's modification of partial least squares for multiple predictands. The balance of ingredients can be chosen by cross-validation, as can the number of regressors constructed. The new method has been tested on real and simulated data. The indications are that conditions for the superiority of the joint approach may be rare in practice.
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