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)