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http://dx.doi.org/10.5351/KJAS.2014.27.1.031

Independent Component Biplot  

Lee, Su Jin (Department of Statistics, Pusan National University)
Choi, Yong-Seok (Department of Statistics, Pusan National University)
Publication Information
The Korean Journal of Applied Statistics / v.27, no.1, 2014 , pp. 31-41 More about this Journal
Abstract
Biplot is a useful graphical method to simultaneously explore the rows and columns of a two-way data matrix. In particular, principal component factor biplot is a graphical method to describe the interrelationship among many variables in terms of a few underlying but unobservable random variables called factors. If we consider the unobservable variables (which are mutually independent and also non-Gaussian), we can apply the independent component analysis decomposing a mixture of non-Gaussian in its independent components. In this case, if we apply the principal component factor analysis, we cannot clearly describe the interrelationship among many variables. Therefore, in this study, we apply the independent component analysis of Jutten and Herault (1991) decomposing a mixture of non-Gaussian in its independent components. We suggest an independent component biplot to interpret the independent component analysis graphically.
Keywords
Biplot; independent component analysis; non-Gaussian;
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