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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: | 2.0.1 |
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: | 2022-09-05 |
DOI: | 10.32614/CRAN.package.latentcor |
Author: | Mingze Huang [aut, cre], Grace Yoon [aut], Christian Müller [aut], Irina Gaynanova [aut] |
Maintainer: | Mingze Huang <mingzehuang at gmail.com> |
License: | GPL-3 |
NeedsCompilation: | yes |
Materials: | README NEWS |
CRAN checks: | latentcor results |
Reference manual: | latentcor.pdf |
Vignettes: |
latentcor Mathematical Framework for latentcor |
Package source: | latentcor_2.0.1.tar.gz |
Windows binaries: | r-devel: latentcor_2.0.1.zip, r-release: latentcor_2.0.1.zip, r-oldrel: latentcor_2.0.1.zip |
macOS binaries: | r-release (arm64): latentcor_2.0.1.tgz, r-oldrel (arm64): latentcor_2.0.1.tgz, r-release (x86_64): latentcor_2.0.1.tgz, r-oldrel (x86_64): latentcor_2.0.1.tgz |
Old sources: | latentcor archive |
Reverse imports: | mixedCCA |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.