CoFM: Copula Factor Models
Abstract
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) .
Fields of Study & Subjects
Financial Risk and Volatility Modeling
Statistical Methods and Applications
Statistical Methods and Inference
Publication details
- Publication date
- 27 January 2026
- Document type
- Dataset