mixedCCA: 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) <doi:10.1093/biomet/asaa007> and Yoon, Müller and Gaynanova (2020) <arXiv:2006.13875>.

Getting started

Package details

AuthorGrace Yoon [aut] (<https://orcid.org/0000-0003-3263-1352>), Irina Gaynanova [aut, cre] (<https://orcid.org/0000-0002-4116-0268>)
MaintainerIrina Gaynanova <irinag@stat.tamu.edu>
Package repositoryView on CRAN
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mixedCCA documentation built on March 21, 2021, 1:07 a.m.