Partial least squares for simultaneous reduction of response and predictor vectors in regression

R. Dennis Cook, Liliana Forzani and Lan Liu

Journal of Multivariate Analysis, 2023, vol. 196, issue C

Abstract: We study and establish a foundation for dimension reduction methods that compress the response and predictor vectors in multivariate regression. While all of the methods studied can perform competitively, depending on the characteristics of the regression, using partial least squares to compress the response and predictor vectors was judged to be the best for prediction and parameter estimation.

Keywords: Envelopes; NIPALS; Sufficient dimension reduction; Two-block method (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.jmva.2023.105163

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