# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "latentcor" in publications use:' type: software license: GPL-3.0-only title: 'latentcor: Fast Computation of Latent Correlations for Mixed Data' version: 2.0.1 doi: 10.32614/CRAN.package.latentcor abstract: 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., Müller C.L. and Gaynanova I. (2021) . The latter method uses multi-linear interpolation originally implemented in the R package . authors: - family-names: Huang given-names: Mingze email: mingzehuang@gmail.com orcid: https://orcid.org/0000-0003-3919-1564 - family-names: Yoon given-names: Grace email: gyoon6067@gmail.com orcid: https://orcid.org/0000-0003-3263-1352 - family-names: Müller given-names: Christian email: christian.mueller@stat.uni-muenchen.de orcid: https://orcid.org/0000-0002-3821-7083 - family-names: Gaynanova given-names: Irina email: irinag@stat.tamu.edu orcid: https://orcid.org/0000-0002-4116-0268 repository: https://mingzehuang.r-universe.dev commit: 4e47d04a6f6f5257a10e28b46718c58a498dce25 contact: - family-names: Huang given-names: Mingze email: mingzehuang@gmail.com orcid: https://orcid.org/0000-0003-3919-1564