Collinearity and multivariable analysis

Multivariable and Vector Analysis

c © W W L Chen, 1997, 2008. This chapter is available free to all individuals, on the understanding that it is not to be used for financial gain, and may be downloaded and/or photocopied, with or without permission from the author. However, this document may not be kept on any information storage and retrieval system without permission from the author, unless such system is not accessible to an...

Collinearity analysis of allotetraploid Gossypium tomentosum and Gossypium darwinii.

Gossypium tomentosum and G. darwinii are wild allotetraploid cotton species, characterized by many excellent traits, including fiber fineness, drought tolerance, and Fusarium and Verticillium wilt resistance. Based on the construction of F2 linkage groups of G. hirsutum x G. tomentosum and G. hirsutum x G. darwinii, two genetic linkage maps were compared. As a result, we found a total of seven ...

Understanding the collinearity problem in regression and discriminant analysis

This paper presents a discussion of the collinearity problem in regression and discriminant analysis. The paper describes reasons why the collinearity is a problem for the prediction ability and classification ability of the classical methods. The discussion is based on established formulae for prediction errors. Special emphasis is put on differences and similarities between regression and cla...

Collinearity, Power, and Interpretation of Multiple Regression Analysis

Collinearity and Least Squares Regression

abstract In this paper we introduce certain numbers, called collinearity indices, which are useful in detecting near collinearities in regression problems. The coeecients enter adversely into formulas concerning signiicance testing and the eeects of errors in the regression variables. Thus they provide simple regression diagnostics, suitable for incorporation in regression packages.