Statistical Software SAMMIF for Sensitivity Analysis in Multivariate Methods

Yuichi Mori, Shingo Watadani, Yoshiro Yamamoto, Tomoyuki Tarumi and Yutaka Tanaka
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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

A chapter in Measurement and Multivariate Analysis, 2002, pp 279-288 from Springer

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.

Keywords: Canonical Correlation Analysis; Influence Function; Multivariate Method; Principal Component Score; Perform Sensitivity Analysis (search for similar items in EconPapers)
Date: 2002
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-4-431-65955-6_30

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DOI: 10.1007/978-4-431-65955-6_30

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