International audienceCanonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations between two datasets acquired on the same experimental units. The cancor () function in R (R Development Core Team 2007) performs the core of computations but further work was required to provide the user with additional tools to facilitate the interpretation of the results. We implemented an R package, CCA, freely available from the Comprehensive R Archive Network (CRAN, http://CRAN.R-project.org/), to develop numerical and graphical outputs and to enable the user to handle missing values. The CCA package also includes a regularized version of CCA to deal with datasets with more variables than units. Illustrations are ...
R-script behind the Canonical Correlation Analyses (CCA) presented in Table 2 and Table S6
OBJECTIVE: Canonical correlation analysis (CCA) is a data-driven method that has been successfully u...
Canonical Correlation Analysis Model Zoo: Standard: CCA, GCCA, MCCA, TCCA, KCCA, TKCCA, sparse CCA ,...
Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations...
Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations...
Canonical correlations analysis (CCA) is an exploratory statistical method to high-light correlation...
Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations...
Canonical correlation analysis (CCA) is a method for describing the relationship between two multiva...
Canonical correlation analysis (CCA) is a natural generalization of PCA when the data contain two se...
Canonical Correlation Analysis (CCA) is a multivariate technique that takes two datasets and forms t...
Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Pr...
Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Pr...
Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Pr...
Canonical Correlation Analysis Zoo: CCA, GCCA (weighted/missing observations), MCCA, DCCA, DMCCA, DG...
Canonical Correlation Analysis (CCA) can be conceptualized as a multivariate regression involving mu...
R-script behind the Canonical Correlation Analyses (CCA) presented in Table 2 and Table S6
OBJECTIVE: Canonical correlation analysis (CCA) is a data-driven method that has been successfully u...
Canonical Correlation Analysis Model Zoo: Standard: CCA, GCCA, MCCA, TCCA, KCCA, TKCCA, sparse CCA ,...
Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations...
Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations...
Canonical correlations analysis (CCA) is an exploratory statistical method to high-light correlation...
Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations...
Canonical correlation analysis (CCA) is a method for describing the relationship between two multiva...
Canonical correlation analysis (CCA) is a natural generalization of PCA when the data contain two se...
Canonical Correlation Analysis (CCA) is a multivariate technique that takes two datasets and forms t...
Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Pr...
Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Pr...
Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Pr...
Canonical Correlation Analysis Zoo: CCA, GCCA (weighted/missing observations), MCCA, DCCA, DMCCA, DG...
Canonical Correlation Analysis (CCA) can be conceptualized as a multivariate regression involving mu...
R-script behind the Canonical Correlation Analyses (CCA) presented in Table 2 and Table S6
OBJECTIVE: Canonical correlation analysis (CCA) is a data-driven method that has been successfully u...
Canonical Correlation Analysis Model Zoo: Standard: CCA, GCCA, MCCA, TCCA, KCCA, TKCCA, sparse CCA ,...