{ "_id": "6a1eff35b401979e7341a983", "Package": "FARS", "Type": "Package", "Title": "Factor-Augmented Regression Scenarios", "Version": "0.8.0", "Authors@R": "c(person(\"Gian Pietro\", \"Bellocca\", email = \"gbellocc@est-econ.uc3m.es\", role = c(\"aut\", \"cre\")),\nperson(\"Ignacio\", \"Garrón\", role = c(\"aut\")),\nperson(\"Vladimir\", \"Rodríguez-Caballero\", role = c(\"aut\")),\nperson(\"Esther\", \"Ruiz\", role = c(\"aut\")))", "Maintainer": "Gian Pietro Bellocca ", "Description": "Provides a comprehensive framework in R for modeling and\nforecasting economic scenarios based on multi-level dynamic\nfactor model. The package enables users to: (i) extract global\nand group-specific factors using a flexible multi-level factor\nstructure; (ii) compute asymptotically valid confidence regions\nfor the estimated factors, accounting for uncertainty in the\nfactor loadings; (iii) obtain estimates of the parameters of\nthe factor-augmented quantile regressions together with their\nstandard deviations; (iv) recover full predictive conditional\ndensities from estimated quantiles; (v) obtain risk measures\nbased on extreme quantiles of the conditional densities; (vi)\nestimate the conditional density and the corresponding extreme\nquantiles when the factors are stressed.", "VignetteBuilder": "R.rsp", "License": "GPL (>= 2)", "Encoding": "UTF-8", "RoxygenNote": "7.3.2", "URL": "https://arxiv.org/abs/2507.10679", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-18 09:18:27 UTC", "User": "root" }, "Author": "Gian Pietro Bellocca [aut, cre], Ignacio Garrón [aut], Vladimir\nRodríguez-Caballero [aut], 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