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latentcor
View on CRAN: Click
here
Download and install latentcor package within the R console
Install from CRAN:
install.packages("latentcor")
Install from Github:
library("remotes")
install_github("cran/latentcor")
Install by package version:
library("remotes")
install_version("latentcor", "2.0.1")
Attach the package and use:
library("latentcor")
Maintained by
Mingze Huang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-08-26
Latest Update: 2022-09-05
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).
For ternary type, see Quan X., Booth J.G. and Wells M.T. (2018) .
For truncated type or zero-inflated type, see Yoon G., Carroll R.J. and Gaynanova I. (2020) .
For approximation method of computation, see Yoon G., M
How to cite:
Mingze Huang (2021). latentcor: Fast Computation of Latent Correlations for Mixed Data. R package version 2.0.1, https://cran.r-project.org/web/packages/latentcor. Accessed 22 Dec. 2024.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for latentcor
Functions, R codes and Examples using
the latentcor R package
Some associated functions: evaluation . gen_data . get_types . interpolant . interpolation . ipol . latentcor . mlappx.real . r_ml_wrapper .
Some associated R codes: evaluation.R . gen_data.R . get_types.R . internal.R . interpolant.R . interpolation.R . ipol.R . latentcor.R . multilinear.R . tools.R . Full latentcor package functions and examples
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