Provides a comprehensive framework in R for modeling and forecasting economic scenarios based on multi-level dynamic factor model. The package enables users to: (i) extract global and block-specific factors using a flexible multilevel factor structure; (ii) compute asymptotically valid confidence regions for the estimated factors, accounting for uncertainty in the factor loadings; (iii) estimate factor-augmented quantile regressions; (iv) recover full predictive densities from these quantile forecasts; and (v) estimate the density when the factors are stressed.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | ggplot2, plotly, sn, nloptr, ellipse, SyScSelection, quantreg, tidyr, dplyr, forcats, MASS, reshape2 |
| Suggests: | devtools, knitr, rmarkdown, openxlsx, readxl, zoo |
| Published: | 2025-04-03 |
| DOI: | 10.32614/CRAN.package.FARS |
| Author: | Gian Pietro Bellocca [aut, cre], Ignacio Garrón [aut], Vladimir Rodríguez-Caballero [aut], Esther Ruiz [aut] |
| Maintainer: | Gian Pietro Bellocca <gbellocc at est-econ.uc3m.es> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | FARS results |
| Reference manual: | FARS.pdf |
| Vignettes: |
introduction (source, R code) |
| Package source: | FARS_0.1.0.tar.gz |
| Windows binaries: | r-devel: FARS_0.1.0.zip, r-release: FARS_0.1.0.zip, r-oldrel: FARS_0.1.0.zip |
| macOS binaries: | r-release (arm64): FARS_0.1.0.tgz, r-oldrel (arm64): FARS_0.1.0.tgz, r-release (x86_64): FARS_0.1.0.tgz, r-oldrel (x86_64): FARS_0.1.0.tgz |
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