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mixedCCA
View on CRAN: Click
here
Download and install mixedCCA package within the R console
Install from CRAN:
install.packages("mixedCCA")
Install from Github:
library("remotes")
install_github("cran/mixedCCA") Install by package version:
library("remotes")
install_version("mixedCCA", "1.6.3") Attach the package and use:
library("mixedCCA")
Maintained by
Irina Gaynanova
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-08-26
Latest Update: 2022-09-09
Description:
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, Mueller and Gaynanova (2021) .
How to cite:
Irina Gaynanova (2020). mixedCCA: Sparse Canonical Correlation Analysis for High-Dimensional Mixed Data. R package version 1.6.3, https://cran.r-project.org/web/packages/mixedCCA. Accessed 05 Aug. 2026.
Previous versions and publish date:
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Complete documentation for mixedCCA
Functions, R codes and Examples using
the mixedCCA R package
Some associated functions: CorrStructure . GenerateData . KendallTau . estimateR . find_w12bic . lambdaseq_generate . mixedCCA . myrcc . standardCCA .
Some associated R codes: GenerateData.R . KendallCCA.R . KendallTau.R . RcppExports.R . auxiliaryFunctions.R . bridge.R . bridgeInv.R . estimateR.R . fromKtoR.R . fromKtoR_ml.R . Full mixedCCA package functions and examples
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