Principal component analysis in an asymmetric norm. (English) Zbl 1418.62249
J. Multivariate Anal. 171, 1-21 (2019); corrigendum ibid. 177, Article ID 104564, 1 p. (2020).
The generalization of the PCA is proposed for quantiles and expectiles. Under the elliptically symmetric distributions it turns to the convential PCA. The proposed approach is suitable to study extremes of the multivariate data. Experiments with weather datasets illustrate the efficiency of the proposed method.
Reviewer: Denis Sidorov (Irkutsk)
MSC:
| 62H25 | Factor analysis and principal components; correspondence analysis |
| 62G08 | Nonparametric regression and quantile regression |
Software:
fda (R)References:
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