An entropy-based tool to help the interpretation of common-factor spaces in factor analysis

Nobuoki Eshima, Claudio Giovanni Borroni, Minoru Tabata, Takeshi Kurosawa

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes a method for deriving interpretable common factors based on canonical correlation analysis applied to the vectors of common factors and manifest variables in the factor analysis model. First, an entropy-based method for measuring factor contributions is reviewed. Second, the entropy-based contribution measure of the common-factor vector is decomposed into those of canonical common factors, and it is also shown that the importance order of factors is that of their canonical correlation coefficients. Third, the method is applied to derive interpretable common factors. Numerical examples are provided to demonstrate the usefulness of the present approach.

Original languageEnglish
Article number140
Pages (from-to)1-13
Number of pages13
JournalEntropy
Volume23
Issue number2
DOIs
Publication statusPublished - Feb 2021

Keywords

  • Canonical common factor
  • Canonical factor analysis
  • Entropy
  • Factor contribution

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