A great number of procedures for sparse principal component analysis (PCA) were proposed in the last decade. However, they cannot be applied directly for PCA of compositional data (CoDa). We introduce a new procedure for sparse PCA which takes into account the additional constraints specific for CoDa. The proposed method is very effective to find logcontrasts in data, which is illustrated on a real example.

Sparse PCA for compositional data

GALLO, Michele
2014-01-01

Abstract

A great number of procedures for sparse principal component analysis (PCA) were proposed in the last decade. However, they cannot be applied directly for PCA of compositional data (CoDa). We introduce a new procedure for sparse PCA which takes into account the additional constraints specific for CoDa. The proposed method is very effective to find logcontrasts in data, which is illustrated on a real example.
2014
9788884678744
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11574/96014
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