A clustering approach to interpretable principal components

DOI10.1080/02664763.2012.749846OpenAlexW2141857460MaRDI QIDQ5128940

Nickolay T. Trendafilov, Doyo G. Enki, Ian T. Jolliffe

Publication date: 26 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2012.749846

zbMATH Keywords

eigenvaluesinterpretationclustering variablessparse principal componentsweighted variances

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

Robustness of interpretable components in relation to the effect of outliers using measures and circular distances, Advances in principal balances for compositional data, From simple structure to sparse components: a review, An empirical comparison of two approaches for CDPCA in high-dimensional data

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