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 group-specific factors using a flexible multi-level factor structure; (ii) compute asymptotically valid confidence regions for the estimated factors, accounting for uncertainty in the factor loadings; (iii) obtain estimates of the parameters of the factor-augmented quantile regressions together with their standard deviations; (iv) recover full predictive conditional densities from estimated quantiles; (v) obtain risk measures based on extreme quantiles of the conditional densities; (vi) estimate the conditional density and the corresponding extreme quantiles when the factors are stressed.
| Version: |
0.6.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
rlang, magrittr, ggplot2, plotly, sn, nloptr, ellipse, SyScSelection, quantreg, tidyr, dplyr, forcats, MASS, reshape2, stringr |
| Suggests: |
R.rsp, devtools, knitr, rmarkdown, markdown, openxlsx, readxl, zoo |
| Published: |
2025-10-07 |
| 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)] |
| URL: |
https://arxiv.org/abs/2507.10679 |
| NeedsCompilation: |
no |
| Citation: |
FARS citation info |
| Materials: |
README |
| CRAN checks: |
FARS results |