Sparse Canonical Correlation Analysis for High-Dimensional Mixed Data

Semi-parametric approach for sparse canonical correlation analysis which can handle mixed data types: continuous, binary and truncated continuous. Bridge functions are provided to connect Kendall's tau to latent correlation under the Gaussian copula model. The methods are described in Yoon, Carroll and Gaynanova (2020) and Yoon, Müller and Gaynanova (2020) .


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install.packages("mixedCCA")

1.4.3 by Grace Yoon, 9 days ago


Browse source code at https://github.com/cran/mixedCCA


Authors: Grace Yoon [aut, cre] , Irina Gaynanova [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports Rcpp, pcaPP, Matrix, fMultivar, mnormt, irlba, chebpol

Depends on stats, MASS

Linking to Rcpp, RcppArmadillo


See at CRAN