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http://dx.doi.org/10.5351/KJAS.2007.20.2.345

Visualizing (X,Y) Data by Partial Least Squares Method  

Huh, Myung-Hoe (Department of Statistics, Korea University)
Lee, Yong-Goo (Department of Statistics, Chung-Ang University)
Yi, Seong-Keun (Department of Business Administration, Sungshin Women's Univeristy)
Publication Information
The Korean Journal of Applied Statistics / v.20, no.2, 2007 , pp. 345-355 More about this Journal
Abstract
PLS methods are suited for regressing q-variate Y variables on p-variate X variables even in the presence of multicollinearity problem among X variables. Consequently, they are useful for analyzing datasets with smaller number of observations compared to the number of variables, such as NIR(near-infrared) spectroscopy data in chemometrics. In this study, we propose two visualizing methods of p-variate X variables and q-variate Y variable that can be used in connection with PLS analysis.
Keywords
PLS regression; data visualization; quantification plot;
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