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.
- Version1.6.2
- R versionunknown
- LicenseGPL-3
- Needs compilation?Yes
- Last release09/09/2022
Documentation
Team
Irina Gaynanova
MaintainerShow author detailsMingze Huang
Show author detailsRolesContributorGrace Yoon
Insights
Last 30 days
This package has been downloaded 394 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 16 times.
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Last 365 days
This package has been downloaded 4,807 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 43 downloads.
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Dependencies
- Depends1 package
- Imports7 packages
- Linking To2 packages