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FARS  

Factor-Augmented Regression Scenarios
View on CRAN: Click here


Download and install FARS package within the R console
Install from CRAN:
install.packages("FARS")

Install from Github:
library("remotes")
install_github("cran/FARS")

Install by package version:
library("remotes")
install_version("FARS", "0.1.0")



Attach the package and use:
library("FARS")
Maintained by
Gian Pietro Bellocca
[Scholar Profile | Author Map]
First Published: 2025-04-03
Latest Update: 2025-04-03
Description:
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.
How to cite:
Gian Pietro Bellocca (2025). FARS: Factor-Augmented Regression Scenarios. R package version 0.1.0, https://cran.r-project.org/web/packages/FARS. Accessed 04 May. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited FARS R package
View FARS citation profile
Other R packages that FARS depends, imports, suggests or enhances
Complete documentation for FARS
Functions, R codes and Examples using the FARS R package
Full FARS package functions and examples
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