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CoFM: Copula Factor Models

Provides tools for factor analysis in high-dimensional settings under copula-based factor models. It includes functions to simulate factor-model data with copula-distributed idiosyncratic errors (e.g., Clayton, Gumbel, Frank, Student t and Gaussian copulas) and to perform diagnostic tests such as the Kaiser-Meyer-Olkin measure and Bartlett's test of sphericity. Estimation routines include principal component based factor analysis, projected principal component analysis, and principal orthogonal complement thresholding for large covariance matrix estimation. The philosophy of the package is described in Guo G. (2023) <doi:10.1007/s00180-022-01270-z>.

Version: 1.1.4
Depends: R (≥ 3.5.0)
Imports: MASS, psych, copula, matrixcalc, stats
Suggests: testthat (≥ 3.0.0), spelling
Published: 2026-01-27
DOI: 10.32614/CRAN.package.CoFM (may not be active yet)
Author: Guangbao Guo [aut, cre], Xin Gao [aut]
Maintainer: Guangbao Guo <ggb11111111 at 163.com>
License: MIT + file LICENSE
NeedsCompilation: no
Language: en-US
CRAN checks: CoFM results

Documentation:

Reference manual: CoFM.html , CoFM.pdf

Downloads:

Package source: CoFM_1.1.4.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): CoFM_1.1.4.tgz, r-oldrel (arm64): CoFM_1.1.4.tgz, r-release (x86_64): CoFM_1.1.4.tgz, r-oldrel (x86_64): CoFM_1.1.4.tgz

Linking:

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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.