latentcor

The first stand-alone R package for computation of latent correlation that takes into account all variable types (continuous/binary/ordinal/zero-inflated), comes with an optimized memory footprint, and is computationally efficient, essentially making latent correlation estimation almost as fast as rank-based correlation estimation. The estimation is based on latent copula Gaussian models. For continuous/binary types, see Fan, J., Liu, H., Ning, Y., and Zou, H. (2017). For ternary type, see Quan X., Booth J.G. and Wells M.T. (2018) doi:10.48550/arXiv.1809.06255. For truncated type or zero-inflated type, see Yoon G., Carroll R.J. and Gaynanova I. (2020) doi:10.1093/biomet/asaa007. For approximation method of computation, see Yoon G., Müller C.L. and Gaynanova I. (2021) doi:10.1080/10618600.2021.1882468. The latter method uses multi-linear interpolation originally implemented in the R package https://cran.r-project.org/package=chebpol.

Last 30 days

This package has been downloaded 1,103 times in the last 30 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 23 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 10,192 times in the last 365 days. The academic equivalent of having a dedicated subreddit. There are fans, and maybe even a few trolls! The day with the most downloads was Apr 23, 2024 with 85 downloads.

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