%0 Journal Article
%A Shahini, Amir
%A Sarmad, Majid
%T Partial Least Squares Regression
%J Iranian Journal of Official Statistics Studies
%V 20
%N 2
%U http://ijoss.srtc.ac.ir/article-1-79-en.html
%R
%D 2010
%K Cross validation, prediction, multicollinearity, component, PLS,
%X In different researches, we deal with problems that need to predict the behavior of a response variable by a set of explanatory variables. Multiple regression is one of the statistical methods that is widely used in these type of situations. When there is a linear relation between explanatory variables we will faced with multi-collinearity problem that causes ordinary least squares estimators of regression coefficients not to be robust. Partial least squares regression is a multivariate method that used when there is high collinearity between explanatory variables. In this paper, this method is introduced.
%> http://ijoss.srtc.ac.ir/article-1-79-en.pdf
%P 289-304
%& 289
%!
%9 Research
%L A-10-1-55
%+
%G eng
%@ 2538-5798
%[ 2010