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) <doi:10.1093/biomet/asaa007> and Yoon, Mueller and Gaynanova (2021) <doi:10.1080/10618600.2021.1882468>.
Version: 1.6.2 Depends: R (≥ 3.0.1), stats, MASS Imports: Rcpp, pcaPP, Matrix, fMultivar, mnormt, irlba, latentcor (≥ 2.0.1) LinkingTo: Rcpp, RcppArmadillo Published: 2022-09-09 DOI: 10.32614/CRAN.package.mixedCCA Author: Grace Yoon [aut], Mingze Huang [ctb], Irina Gaynanova [aut, cre] Maintainer: Irina Gaynanova <irinag at stat.tamu.edu> License: GPL-3 NeedsCompilation: yes Materials: README CRAN checks: mixedCCA results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=mixedCCA to link to this page.
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