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Biplots in Reduced‐Rank Regression
Author(s) -
Braak Cajo J. F. Ter,
Looman Caspar W. N.
Publication year - 1994
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710360812
Subject(s) - biplot , statistics , regression analysis , mathematics , regression , rank (graph theory) , principal component regression , regression diagnostic , linear regression , partial least squares regression , polynomial regression , biology , biochemistry , combinatorics , gene , genotype
Regression problems with a number of related response variables are typically analyzed by separate multiple regressions. This paper shows how these regressions can be visualized jointly in a biplot based on reduced‐rank regression. Reduced‐rank regression combines multiple regression and principal components analysis and can therefore be carried out with standard statistical packages. The proposed biplot highlights the major aspects of the regressions by displaying the least‐squares approximation of fitted values, regression coefficients and associated t ‐ratios. The utility and interpretation of the reduced‐rank regression biplot is demonstrated with an example using public health data that were previously analyzed by separate multiple regressions.