Copula Factor Models
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 11
- Examples that run
- 100%10 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 9%
Downloads
Dependencies
Installing CoFM adds 13 packages (7 with compiled code, 9.8 MB of source tarballs). Heaviest: copula 3.5 MB, colorspace 2.0 MB, GPArotation 1.6 MB.
Code & Tests
Datasets
People & History
- RR 4.6.0 released · 2026-04-24
- 1.1.4Latest2026-01-27 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-01-27
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 149 KB / 1 file
- Download size
- 167 KB
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