Principal component of explained variance (PCEV) is a statistical tool for the analysis of a multivariate response vector. It is a dimension- reduction technique, similar to Principal component analysis (PCA), that seeks to maximize the proportion of variance (in the response vector) being explained by a set of covariates.
|Author||Maxime Turgeon [aut, cre], Aurelie Labbe [aut], Karim Oualkacha [aut], Stepan Grinek [aut]|
|Date of publication||2017-10-11 03:30:56 UTC|
|Maintainer||Maxime Turgeon <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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