latentcor
Fast Computation of Latent Correlations for Mixed Data
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.0.2 |
rolling linux/jammy R-4.5 | latentcor_2.0.2.tar.gz |
3.0 MiB |
2.0.2 |
rolling linux/noble R-4.5 | latentcor_2.0.2.tar.gz |
3.0 MiB |
2.0.2 |
rolling source/ R- | latentcor_2.0.2.tar.gz |
2.9 MiB |
2.0.2 |
latest linux/jammy R-4.5 | latentcor_2.0.2.tar.gz |
3.0 MiB |
2.0.2 |
latest linux/noble R-4.5 | latentcor_2.0.2.tar.gz |
3.0 MiB |
2.0.2 |
latest source/ R- | latentcor_2.0.2.tar.gz |
2.9 MiB |
2.0.2 |
2026-04-26 source/ R- | latentcor_2.0.2.tar.gz |
2.9 MiB |
2.0.2 |
2026-04-23 source/ R- | latentcor_2.0.2.tar.gz |
2.9 MiB |
2.0.2 |
2026-04-09 windows/windows R-4.5 | latentcor_2.0.2.zip |
3.1 MiB |
2.0.1 |
2025-04-20 source/ R- | latentcor_2.0.1.tar.gz |
2.9 MiB |