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:: Volume 20, Issue 2 (3-2010) ::
مجله‌ی بررسی‌ها 2010, 20(2): 289-304 Back to browse issues page
Partial Least Squares Regression
Amir Shahini * , Majid Sarmad
Abstract:   (4038 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.

Keywords: Cross validation, prediction, multicollinearity, component, PLS
Full-Text [PDF 404 kb]   (3494 Downloads)    
Type of Study: Research | Subject: General
Received: 2009/09/8 | Accepted: 2009/12/23 | Published: 2016/01/10
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Shahini A, Sarmad M. Partial Least Squares Regression. مجله‌ی بررسی‌ها 2010; 20 (2) :289-304
URL: http://ijoss.srtc.ac.ir/article-1-79-en.html


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Volume 20, Issue 2 (3-2010) Back to browse issues page
مجله‌ی بررسی‌های آمار رسمی ایران Ijoss Iranian Journal of Official Statistics Studies
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