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>.
| Version: | 2.0.2 |
| Depends: | R (≥ 3.0.0) |
| Imports: | stats,pcaPP,fMultivar,mnormt,Matrix,MASS,heatmaply,ggplot2,plotly, graphics,geometry,doFuture,foreach,future,doRNG,microbenchmark |
| Suggests: | rmarkdown,markdown,knitr,testthat (≥ 3.0.0),lattice,cubature,plot3D,covr |
| Published: | 2025-11-26 |
| DOI: | 10.32614/CRAN.package.latentcor |
| Author: | Mingze Huang [aut], Grace Yoon [aut], Christian Müller [aut], Irina Gaynanova [aut, cre] |
| Maintainer: | Irina Gaynanova <irinagn at umich.edu> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| Materials: | README,NEWS |
| CRAN checks: | latentcor results |
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