CRAN/E | mixedCCA

mixedCCA

Sparse Canonical Correlation Analysis for High-Dimensional Mixed Data

Installation

About

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.

Key Metrics

Version 1.6.2
R ≥ 3.0.1
Published 2022-09-09 603 days ago
Needs compilation? yes
License GPL-3
CRAN checks mixedCCA results

Downloads

Yesterday 16 -6%
Last 7 days 121 -19%
Last 30 days 441 +16%
Last 90 days 1.175 -7%
Last 365 days 4.638 +3%

Maintainer

Maintainer

Irina Gaynanova

irinag@stat.tamu.edu

Authors

Grace Yoon

aut

Mingze Huang

ctb

Irina Gaynanova

aut / cre

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

mixedCCA archive

Depends

R ≥ 3.0.1
stats
MASS

Imports

Rcpp
pcaPP
Matrix
fMultivar
mnormt
irlba
latentcor ≥2.0.1

LinkingTo

Rcpp
RcppArmadillo