Generalized canonical correlation (original) (raw)
In statistics, the generalized canonical correlation analysis (gCCA), is a way of making sense of cross-correlation matrices between the sets of random variables when there are more than two sets. While a conventional CCA generalizes principal component analysis (PCA) to two sets of random variables, a gCCA generalizes PCA to more than two sets of random variables. The canonical variables represent those common factors that can be found by a large PCA of all of the transformed random variables after each set underwent its own PCA.
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| dbo:abstract | In statistics, the generalized canonical correlation analysis (gCCA), is a way of making sense of cross-correlation matrices between the sets of random variables when there are more than two sets. While a conventional CCA generalizes principal component analysis (PCA) to two sets of random variables, a gCCA generalizes PCA to more than two sets of random variables. The canonical variables represent those common factors that can be found by a large PCA of all of the transformed random variables after each set underwent its own PCA. (en) L'Analyse canonique généralisée au sens de Caroll (d'après J.D.Caroll) étend l'Analyse canonique ordinaire à l'étude de p Groupes de variables (p > 2) appliquées sur le même espace des individus. Elle admet comme cas particuliers l'ACP, l'AFC et l'ACM, l'Analyse canonique simple, mais aussi la régression simple, et multiple, l'analyse de la variance, l'analyse de la covariance et l'analyse discriminante. (fr) |
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| rdfs:comment | In statistics, the generalized canonical correlation analysis (gCCA), is a way of making sense of cross-correlation matrices between the sets of random variables when there are more than two sets. While a conventional CCA generalizes principal component analysis (PCA) to two sets of random variables, a gCCA generalizes PCA to more than two sets of random variables. The canonical variables represent those common factors that can be found by a large PCA of all of the transformed random variables after each set underwent its own PCA. (en) L'Analyse canonique généralisée au sens de Caroll (d'après J.D.Caroll) étend l'Analyse canonique ordinaire à l'étude de p Groupes de variables (p > 2) appliquées sur le même espace des individus. Elle admet comme cas particuliers l'ACP, l'AFC et l'ACM, l'Analyse canonique simple, mais aussi la régression simple, et multiple, l'analyse de la variance, l'analyse de la covariance et l'analyse discriminante. (fr) |
| rdfs:label | Generalized canonical correlation (en) Analyse canonique généralisée (fr) |
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