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.File in questo prodotto:
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