Package: CoFM 1.1.4

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>.

Authors:Guangbao Guo [aut, cre], Xin Gao [aut]

CoFM_1.1.4.tar.gz
CoFM_1.1.4.zip(r-4.7)CoFM_1.1.4.zip(r-4.6)CoFM_1.1.4.zip(r-4.5)
CoFM_1.1.4.tgz(r-4.6-any)CoFM_1.1.4.tgz(r-4.5-any)
CoFM_1.1.4.tar.gz(r-4.7-any)CoFM_1.1.4.tar.gz(r-4.6-any)
CoFM_1.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
CoFM/json (API)

# Install 'CoFM' in R:
install.packages('CoFM', repos = c('https://guangbaog.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 180 downloads 10 exports 18 dependencies

Last updated from:81e63bb21d. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK131
source / vignettesOK174
linux-release-x86_64OK122
macos-release-arm64OK84
macos-oldrel-arm64OK71
windows-develOK86
windows-releaseOK86
windows-oldrelOK69
wasm-releaseOK103

Exports:CoFMCopula_errorsFanPC_basicFanPC_CoFMPC_CoFMpoetPPC_basicPPC_CoFMPPC_newPPC_u

Dependencies:ADGofTestclustercolorspacecopulaGPArotationgsllatticeMASSMatrixmatrixcalcmnormtmvtnormnlmenumDerivpcaPPpsplinepsychstabledist