Multi-block data analysis concerns the analysis of several sets of variables (blocks) observed on the same group of individuals. The main aims of the RGCCA package are: (i) to study the relationships between blocks and (ii) to identify subsets of variables of each block which are active in their relationships with the other blocks.
|Author||Arthur Tenenhaus and Vincent Guillemot|
|Date of publication||2017-01-22 11:25:22|
|Maintainer||Arthur Tenenhaus <firstname.lastname@example.org>|
|License||GPL (>= 2)|
BinarySearch: Internal function which does not have to be used by the users
cov2: Variance and Covariance (Matrices)
defl.select: deflation function
derivation: compute the derivative of the g function
miscrossprod: Cross product function for inputs with missing data.
rgcca: Regularized Generalized Canonical Correlation Analysis...
rgccak: Internal function for computing the RGCCA parameters (RGCCA...
Russett: Russett data
scale2: Scaling and Centering of Matrix-like Objects
sgcca: Variable Selection For Generalized Canonical Correlation...
sgccak: Internal function for computing the SGCCA parameters (SGCCA...
soft: the function soft() encodes the soft-thresholding operator
soft.threshold: The function soft.threshold() soft-thresholds a vector such...
tau.estimate: Optimal shrinkage intensity parameters.