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mixedCCA  

Sparse Canonical Correlation Analysis for High-Dimensional Mixed Data
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", "1.6.2")



Attach the package and use:
library("mixedCCA")
Maintained by
Irina Gaynanova
[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 1.6.2, https://cran.r-project.org/web/packages/mixedCCA. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.3.0 (2020-08-26 11:20), 1.3.1 (2020-08-27 09:20), 1.4.3 (2020-10-12 01:40), 1.4.6 (2021-03-20 23:50), 1.5.2 (2022-05-26 01:10)
Other packages that cited mixedCCA R package
View mixedCCA citation profile
Other R packages that mixedCCA depends, imports, suggests or enhances
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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