Partial Least Squares Regression
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Amir Shahini *, Majid Sarmad |
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Abstract: (3624 Views) |
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. |
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Keywords: Cross validation, prediction, multicollinearity, component, PLS |
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Full-Text [PDF 404 kb]
(3055 Downloads)
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Type of Study: Research |
Subject:
General Received: 2009/09/8 | Accepted: 2009/12/23 | Published: 2016/01/10
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