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) <doi:10.1111/rssb.12168>.
For ternary type, see Quan X., Booth J.G. and Wells M.T. (2018) <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>.

stats, pcaPP, fMultivar, mnormt, chebpol, Matrix, MASS,
heatmaply, ggplot2, plotly, graphics
microbenchmark, rmarkdown, markdown, knitr, testthat (>=
3.0.0), covr

stats, pcaPP, fMultivar, mnormt, Matrix, MASS, heatmaply,
ggplot2, plotly, graphics

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) <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>.
stats, pcaPP, fMultivar, mnormt, Matrix, MASS, heatmaply,
ggplot2, plotly, graphics, geometry, doFuture, foreach, future,
doRNG, microbenchmark
rmarkdown, markdown, knitr, testthat (>= 3.0.0), lattice,
cubature, plot3D, covr