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) .


Reference manual

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1.4.6 by Irina Gaynanova, 7 months ago

Browse source code at

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

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