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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>.

copied from cf-staging / r-mixedcca
Type Size Name Uploaded Downloads Labels
conda 186.7 kB | win-64/r-mixedcca-1.5.2-r40h78deb2a_0.tar.bz2  2 years and 4 months ago 599 main
conda 179.8 kB | win-64/r-mixedcca-1.5.2-r41h78deb2a_0.tar.bz2  2 years and 4 months ago 605 main
conda 175.8 kB | osx-64/r-mixedcca-1.5.2-r40h2a5be82_0.tar.bz2  2 years and 4 months ago 75 main
conda 175.6 kB | osx-64/r-mixedcca-1.5.2-r41h2a5be82_0.tar.bz2  2 years and 4 months ago 79 main
conda 172.6 kB | linux-64/r-mixedcca-1.5.2-r41h9f5de39_0.tar.bz2  2 years and 4 months ago 1683 main
conda 173.0 kB | linux-64/r-mixedcca-1.5.2-r40h9f5de39_0.tar.bz2  2 years and 4 months ago 1668 main

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