sparseDFM
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) <doi:10.1198/016214502388618960>, 2Stage Giannone et al. (2008) <doi:10.1016/j.jmoneco.2008.05.010>, expectation-maximisation (EM) Banbura and Modugno (2014) <doi:10.1002/jae.2306>, and the novel EM-sparse approach for sparse DFMs Mosley et al. (2023) <arXiv:2303.11892>. Options to use classic multivariate Kalman filter and smoother (KFS) equations from Shumway and Stoffer (1982) <doi:10.1111/j.1467-9892.1982.tb00349.x> or fast univariate KFS equations from Koopman and Durbin (2000) <doi:10.1111/1467-9892.00186>, 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'.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0 |
rolling linux/jammy R-4.5 | sparseDFM_1.0.tar.gz |
673.3 KiB |
1.0 |
rolling linux/noble R-4.5 | sparseDFM_1.0.tar.gz |
678.3 KiB |
1.0 |
rolling source/ R- | sparseDFM_1.0.tar.gz |
408.8 KiB |
1.0 |
latest linux/jammy R-4.5 | sparseDFM_1.0.tar.gz |
673.3 KiB |
1.0 |
latest linux/noble R-4.5 | sparseDFM_1.0.tar.gz |
678.3 KiB |
1.0 |
latest source/ R- | sparseDFM_1.0.tar.gz |
408.8 KiB |
1.0 |
2026-04-26 source/ R- | sparseDFM_1.0.tar.gz |
408.8 KiB |
1.0 |
2026-04-23 source/ R- | sparseDFM_1.0.tar.gz |
408.8 KiB |
1.0 |
2026-04-09 windows/windows R-4.5 | sparseDFM_1.0.zip |
1.0 MiB |
1.0 |
2025-04-20 source/ R- | sparseDFM_1.0.tar.gz |
408.8 KiB |