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DESCRIPTION
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DESCRIPTION
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Package: latentcor
Type: Package
Title: Fast Computation of Latent Correlations for Mixed Data
Version: 1.2.0
Authors@R: c(
person(given = "Mingze",
family = "Huang",
role = c("aut", "cre"),
email = "mingzehuang@gmail.com",
comment = c(ORCID = "0000-0003-3919-1564")),
person(given = "Grace",
family = "Yoon",
role = c("aut"),
email = "gyoon6067@gmail.com",
comment = c(ORCID = "0000-0003-3263-1352")),
person(given = "Christian",
family = "Müller",
role = c("aut"),
email = "christian.mueller@stat.uni-muenchen.de",
comment = c(ORCID = "0000-0002-3821-7083")),
person(given = "Irina",
family = "Gaynanova",
role = c("aut"),
email = "irinag@stat.tamu.edu",
comment = c(ORCID = "0000-0002-4116-0268")))
Maintainer: Mingze Huang <mingzehuang@gmail.com>
Description: 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>.
Depends: R (>= 3.0.0)
Imports: stats, pcaPP, fMultivar, mnormt, chebpol, Matrix, MASS, heatmaply, ggplot2, plotly, graphics
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.2
Suggests:
microbenchmark,
rmarkdown,
markdown,
knitr,
testthat (>= 3.0.0),
covr
Config/testthat/edition: 3
VignetteBuilder: knitr