Era,  Masayoshi

Furukawa, Tetsuo

Ishibashi, Hideaki

Isogai,  Hirohisa

Shinriki,  Ryota

The purpose of this research is to develop a method for multilevel-multigroup analysis based on a nonlinear tensor modeling. The aim of the method is to analyze a set of groups by comparing the member variations as well as analyzing the members for each group. For this purpose, the proposed method estimates the member correspondence between the groups, indicating the members who play similar roles or occupy similar positions in each group. To discover the correspondence, the proposed method models each group by a manifold, and aligns them so that they form a smooth fiber bundle. As the result, the method represents the entire data by a third-order product manifold, corresponding to members, groups and survey items. We applied the method to a dataset of football players of university teams.2017 International Workshop on Smart Info-Media Systems in Asia, SISA 2017, 6-8 September, 2017, Kyushu Institute of Information Sciences, Dazaifu City, Fukuoka, Japa

石橋, 英朗

イシバシ, ヒデアキ

古川, 徹生

フルカワ, テツオ

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Multilevel-Multigroup Analysis Discovering Member Correspondence between Groups

Multilevel-Multigroup Analysis Discovering Member Correspondence between Groups

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