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Statistical Software SAMMIF for Sensitivity Analysis in Multivariate Methods

  • Yuichi Mori
  • Shingo Watadani
  • Yoshiro Yamamoto
  • Tomoyuki Tarumi
  • Yutaka Tanaka
Conference paper

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.

Keywords

Canonical Correlation Analysis Influence Function Multivariate Method Principal Component Score Perform Sensitivity Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Japan 2002

Authors and Affiliations

  • Yuichi Mori
    • 1
  • Shingo Watadani
    • 2
  • Yoshiro Yamamoto
    • 3
  • Tomoyuki Tarumi
    • 4
  • Yutaka Tanaka
    • 4
  1. 1.Dept. of Socio-InformationOkayama University of ScienceOkayamaJapan
  2. 2.Dept. of Liberal Arts and ScienceKurashiki University of Science and the ArtsKurashikiJapan
  3. 3.Dept. of Management and Information sciencesTama UniversityTama-shi, TokyoJapan
  4. 4.Dept. of Environmental and Mathematical ScienceOkayama UniversityOkayamaJapan

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