Principal loading analysis

Jan O. Bauer and Bernhard Drabant

Journal of Multivariate Analysis, 2021, vol. 184, issue C

Abstract: This paper proposes a tool for dimension reduction where the dimension of the original space is reduced: the principal loading analysis. Principal loading analysis is a tool to reduce dimensions by discarding variables. The intuition is that variables are dropped which distort the covariance matrix only by a little. Our method is introduced and an algorithm for conducting principal loading analysis is provided. Further, we give bounds for the noise arising in the sample case.

Keywords: Component loading; Dimensionality reduction; Matrix perturbation theory; Principal component analysis (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.jmva.2021.104754

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