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, Mueller and Gaynanova (2021) <doi:10.1080/10618600.2021.1882468>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.6.3 |
rolling linux/jammy R-4.5 | mixedCCA_1.6.3.tar.gz |
141.2 KiB |
1.6.3 |
rolling linux/noble R-4.5 | mixedCCA_1.6.3.tar.gz |
144.1 KiB |
1.6.3 |
rolling source/ R- | mixedCCA_1.6.3.tar.gz |
24.4 KiB |
1.6.3 |
latest linux/jammy R-4.5 | mixedCCA_1.6.3.tar.gz |
141.2 KiB |
1.6.3 |
latest linux/noble R-4.5 | mixedCCA_1.6.3.tar.gz |
144.1 KiB |
1.6.3 |
latest source/ R- | mixedCCA_1.6.3.tar.gz |
24.4 KiB |
1.6.3 |
2026-04-26 source/ R- | mixedCCA_1.6.3.tar.gz |
24.4 KiB |
1.6.3 |
2026-04-23 source/ R- | mixedCCA_1.6.3.tar.gz |
24.4 KiB |
1.6.3 |
2026-04-09 windows/windows R-4.5 | mixedCCA_1.6.3.zip |
467.7 KiB |
1.6.2 |
2025-04-20 source/ R- | mixedCCA_1.6.2.tar.gz |
23.6 KiB |