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Statistical Software SAMMIF for Sensitivity Analysis in Multivariate Methods

In: Measurement and Multivariate Analysis

Author

Listed:
  • Yuichi Mori

    (Okayama University of Science, Dept. of Socio-Information)

  • Shingo Watadani

    (Kurashiki University of Science and the Arts, Dept. of Liberal Arts and Science)

  • Yoshiro Yamamoto

    (Tama University, Dept. of Management and Information sciences)

  • Tomoyuki Tarumi

    (Okayama University, Dept. of Environmental and Mathematical Science)

  • Yutaka Tanaka

    (Okayama University, Dept. of Environmental and Mathematical Science)

Abstract

Summary SAMMIF (Sensitivity Analysis in Multivariate Methods based on Influence Functions) is a statistical package for sensitivity analysis in multivariate methods in which diagnostics statistics are obtained for detecting influential observations and influential directions on the basis of both influence function approach and Cook’s local influence approach. SAMMIF is designed to provide useful graphical user interface and some options for both beginners and specialists. The current version 1.0 performs sensitivity analysis fully in principal component analysis, canonical correlation analysis and exploratory and confirmatory factor analyses with some new diagnostics functions for the analyses. Practical examples illustrate that users can analyze the influence of observations without difficulties.

Suggested Citation

  • Yuichi Mori & Shingo Watadani & Yoshiro Yamamoto & Tomoyuki Tarumi & Yutaka Tanaka, 2002. "Statistical Software SAMMIF for Sensitivity Analysis in Multivariate Methods," Springer Books, in: Shizuhiko Nishisato & Yasumasa Baba & Hamparsum Bozdogan & Koji Kanefuji (ed.), Measurement and Multivariate Analysis, pages 279-288, Springer.
    • Handle: RePEc:spr:sprchp:978-4-431-65955-6_30
    DOI: 10.1007/978-4-431-65955-6_30
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