Generalized data-fitting factor analysis with multiple quantification of categorical variables

Naomichi Makino ()

Computational Statistics, 2015, vol. 30, issue 1, 279-292

Abstract: In this study, a recently proposed data-fitting factor analysis (DFFA) procedure is generalized for categorical variable analysis. For generalized DFFA (GDFFA), we develop an alternating least squares algorithm consisting of a multiple quantification step and a model parameters estimation step. The differences between GDFFA and similar statistical methods such as multiple correspondence analysis and FACTALS are also discussed. The developed algorithm and its solution are illustrated with a real data example. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Data-fitting factor analysis; Categorical variables; Multiple quantification; Multiple correspondence analysis; FACTALS (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:30:y:2015:i:1:p:279-292

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DOI: 10.1007/s00180-014-0536-8

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