A METHOD FOR SELECTION OF VARIABLES IN THE PRINCIPAL COMPONENTS REGRESSION
Fernando
FERRARI[1]
Antonio
Francisco IEMMA[2]
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ABSTRACT: In this paper we
present a method for selection of variables in the principal components
regression in the presence of multicollinearity. This method removes
independent variables of the regression model taking in consideration the
magnitude of the eigenvalues of the matrix X*’X*, where X* = [Y, X], and the
prediction efficacy of independent variables on the response variable.
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KEYWORDS: Multiple linear
regression; multicollinearity; principal components.