Sparse Factor Analysis

Kohei Adachi ()
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Kohei Adachi: Osaka University, Graduate School of Human Sciences

Chapter Chapter 22 in Matrix-Based Introduction to Multivariate Data Analysis, 2020, pp 361-382 from Springer

Abstract: Abstract In the last chapter, modifiedSparse Factor Analysis (SFA) regression analysisRegression analysis procedures were presented, in which a coefficient vectorVector is estimated so that it is sparse, i.e., includes a number of zero elementsElement. Such sparse estimationSparse estimation can be incorporated into other multivariate analysis procedures, so as to provide sparse solutions. They can be easily interpreted, as we may only focus on their nonzero elements. As such, a number of sparse multivariate procedures have been developed, following the sparse estimationSparse estimation techniques developed in regression.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-15-4103-2_22

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DOI: 10.1007/978-981-15-4103-2_22

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