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Variable Selection and Collinearity

  • Ronald Christensen
Part of the Springer Texts in Statistics book series (STS)

Abstract

Suppose we have a set of variables y, x l,...,x s and observations on these variables y 1, x i l,..., x is , i = 1,..., n. We want to identify which of the independent variables, x j , are important in a regression for y. There are several methods available for doing this.

Keywords

Variable Selection Design Matrix Forward Selection Ridge Regression Principal Component Regression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Ronald Christensen
    • 1
  1. 1.Department of Mathematics and StatisticsUniversity of New MexicoAlbuquerqueUSA

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