Fast Computation of Latent Correlations for Mixed Data

Estimation of latent correlations with mixed data types:continuous, binary, truncated (or zero-inflated) and ternary. 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., Müller C.L. and Gaynanova I. (2021) .


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.0.0 by Mingze Huang, a month ago

Browse source code at

Authors: Mingze Huang [aut, cre] , Grace Yoon [aut] , Christian Müller [aut] , Irina Gaynanova [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports stats, rmarkdown, pcaPP, fMultivar, mnormt, chebpol, Matrix, utils, MASS, heatmaply, ggplot2, plotly, graphics, foreach, parallel, doFuture, future, microbenchmark, doRNG

Suggests markdown, knitr, testthat, covr

See at CRAN