Browse > Article
http://dx.doi.org/10.5351/CSAM.2013.20.2.129

Biplots of Multivariate Data Guided by Linear and/or Logistic Regression  

Huh, Myung-Hoe (Department of Statistics, Korea University)
Lee, Yonggoo (Department of Applied Statistics, Chung-Ang University)
Publication Information
Communications for Statistical Applications and Methods / v.20, no.2, 2013 , pp. 129-136 More about this Journal
Abstract
Linear regression is the most basic statistical model for exploring the relationship between a numerical response variable and several explanatory variables. Logistic regression secures the role of linear regression for the dichotomous response variable. In this paper, we propose a biplot-type display of the multivariate data guided by the linear regression and/or the logistic regression. The figures show the directional flow of the response variable as well as the interrelationship of explanatory variables.
Keywords
Data visualization; biplot graph; linear regression; logistic regression; dimensional reduction;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Brownlee, K. A. (1965). Statistical Theory and Methodology in Science and Engineering, Second Edition, Wiley, New York.
2 Gabriel, K. R. (1971). The biplot display of matrices with the application to principal component analysis, Biometrika, 58, 453-467.   DOI   ScienceOn
3 Gower, J. C. and Hand, D. J. (1996). Biplots, Chapman and Hall, London.
4 Greenacre, M. (2010). Biplots in Practice, BBVA Foundation, Madrid.
5 Huh, M. H. (2011a). Exploratory Multivariate Data Analysis, Freedom Academy, Seoul.
6 Huh, M. H. (2011b). Statistical Concepts, Methods and Applications Using R, Freedom Academy, Seoul.
7 Huh, M. H. and Park, H. M. (2009). Visualizing SVM classification in reduced dimensions, Communications of the Korean Statistical Society, 16, 881-889.   과학기술학회마을   DOI   ScienceOn
8 Lebart, L., Morineau, A. and Warwick, K. M. (1984). Multivariate Descriptive Statistical Analysis: Correspondence Analysis and Related Techniques for Large Matrices, Wiley, New York.
9 SAS Inc. (2009). SAS/STAT V9.2 Users Guide, Second Edition. NC: Cary.