Skip to main content

Statistical Software VASMM for Variable Selection in Multivariate Methods

  • Conference paper
Compstat

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

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).

    Google Scholar 

  • 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

    Google Scholar 

  • Krzanowski, W. J. (1987). Selection of variables to preserve multivariate data structure, using principal components. Appl. Statist., 36, 22–33.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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)

    Google Scholar 

  • Rao, C. R. (1964). The use and interpretation of principal component analysis in applied research, Sankhya Ser. A, 26, 329–358.

    MathSciNet  MATH  Google Scholar 

  • Robert, P. and Escoufier, Y. (1976). A unifying tool for linear multivariate statistical methods: the RV-coefficient. Appl. Statist., 25, 257–265.

    Article  MathSciNet  Google Scholar 

  • 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)

    Google Scholar 

  • Tanaka, Y (1983). Some criteria for variable selection in factor analysis, Behaviormetrika, 13, 31–45

    Article  Google Scholar 

  • Tanaka, Y. and Kodake, K. (1981) A method of variable selection in factor analysis and its numerical investigation. Behaviormetrika, 10, 49–61.

    Article  Google Scholar 

  • 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.

    MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints 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

Publish with us

Policies and ethics