Estimate Dynamic Factor Models with Sparse Loadings

Implementation of various estimation methods for dynamic factor models (DFMs) including principal components analysis (PCA) Stock and Watson (2002) , 2Stage Giannone et al. (2008) , expectation-maximisation (EM) Banbura and Modugno (2014) , and the novel EM-sparse approach for sparse DFMs Mosley et al. (2023) . Options to use classic multivariate Kalman filter and smoother (KFS) equations from Shumway and Stoffer (1982) or fast univariate KFS equations from Koopman and Durbin (2000) , and options for independent and identically distributed (IID) white noise or auto-regressive (AR(1)) idiosyncratic errors. Algorithms coded in 'C++' and linked to R via 'RcppArmadillo'.