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: | 0.7.1 |
| 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: | 2025-11-05 |
| 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 |