Abstract
A statistical software package VASMM (VAriable Selection in Multivariate Methods) has been developed for selecting a subset of variables in multivariate methods without external variables. The current version is fully implemented for variable selection in principal component analysis and factor analysis. The system has been constructed with interactive architecture on Internet. The users can not only use the system via a web browser but can also obtain information related to variable selection in multivariate techniques of their choice. It allows for us to perform variable selection easily in a variety of practical applications.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Jolliffe, I. T. (1972, 1973). Discarding variables in a principal component analysis. I, II. Appl. Statist., 21 (160–173), 22 (21–31).
Kano,Y and Harada,A.(2000). Stepwise variable selection in factor analysis, Psychometrika, 65(1), 7–22, URLs: SEFA http://kokol5.hus.osaka-u.ac jp /—ha rada/factor stepwise/, http://koko 16.hus.osaka-u.ac.jp/2harada/scofa/input.html
Krzanowski, W. J. (1987). Selection of variables to preserve multivariate data structure, using principal components. Appl. Statist., 36, 22–33.
Mori, Y., Iizuka, M. Tarumi, T. and Tanaka, Y. (2000). Statistical Software “VASPCA” for Variable Selection in Principal Component Analysis, In: COMPSTAT2000 Proceedings in Computational Statistics (Short Communications) (Edited by Jansen, W. and Bethlehem, J.G.), 73–74.
Mori, Y., Tarumi, T and Tanaka, Y. (1998). Principal Component analysis based on a subset of variables -Numerical investigation on variable selection procedures -. Bulletin of the Computational Statistics of Japan, 11(1), 1–12. (in Japanese)
Rao, C. R. (1964). The use and interpretation of principal component analysis in applied research, Sankhya Ser. A, 26, 329–358.
Robert, P. and Escoufier, Y. (1976). A unifying tool for linear multivariate statistical methods: the RV-coefficient. Appl. Statist., 25, 257–265.
Sano, K., Manaka, S., Kitamura, K., Kagawa, M., Takeuchi, K., Ogashiwa, M., Kameyama, M., Tohgi, H. and Yamada, H. (1977). Statistical studies on evaluation of mind disturbance of consciousness -Abstraction of characteristic clinical pictures by cross-sectional investigation. Sinkei Kenkyu no Shinpo, 21, 1052–1065. (in Japanese)
Tanaka, Y (1983). Some criteria for variable selection in factor analysis, Behaviormetrika, 13, 31–45
Tanaka, Y. and Kodake, K. (1981) A method of variable selection in factor analysis and its numerical investigation. Behaviormetrika, 10, 49–61.
Tanaka, Y and Mori, Y. (1997): Principal component analysis based on a subset of variables: Variable selection and sensitivity analysis. American Journal of Mathematics and Management Sciences, 17, 1&2, 61–89.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Iizuka, M., Mori, Y., Tarumi, T., Tanaka, Y. (2002). Statistical Software VASMM for Variable Selection in Multivariate Methods. In: Härdle, W., Rönz, B. (eds) Compstat. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57489-4_87
Download citation
DOI: https://doi.org/10.1007/978-3-642-57489-4_87
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1517-7
Online ISBN: 978-3-642-57489-4
eBook Packages: Springer Book Archive