Implements state-of-the-art algorithms for the Bayesian analysis of Structural Vector Autoregressions (SVARs) identified by sign, zero, and narrative restrictions. The core model is based on a flexible Vector Autoregression with estimated hyper-parameters of the Minnesota prior and the dummy observation priors as in Giannone, Lenza, Primiceri (2015) <doi:10.1162/REST_a_00483>. The sign restrictions are implemented employing the methods proposed by Rubio-RamÃrez, Waggoner & Zha (2010) <doi:10.1111/j.1467-937X.2009.00578.x>, while identification through sign and zero restrictions follows the approach developed by Arias, Rubio-RamÃrez, & Waggoner (2018) <doi:10.3982/ECTA14468>. Furthermore, our tool provides algorithms for identification via sign and narrative restrictions, in line with the methods introduced by AntolÃn-DÃaz and Rubio-RamÃrez (2018) <doi:10.1257/aer.20161852>. Users can also estimate a model with sign, zero, and narrative restrictions imposed at once. The package facilitates predictive and structural analyses using impulse responses, forecast error variance and historical decompositions, forecasting and conditional forecasting, as well as analyses of structural shocks and fitted values. All this is complemented by colourful plots, user-friendly summary functions, and comprehensive documentation including the vignette by Wang & Woźniak (2024) <doi:10.48550/arXiv.2501.16711>. The 'bsvarSIGNs' package is aligned regarding objects, workflows, and code structure with the R package 'bsvars' by Woźniak (2024) <doi:10.32614/CRAN.package.bsvars>, and they constitute an integrated toolset. It was granted the Di Cook Open-Source Statistical Software Award by the Statistical Society of Australia in 2024.
Version: 2.0 Depends: R (≥ 4.1.0), RcppArmadillo, bsvars Imports: Rcpp (≥ 1.0.12), RcppProgress, R6 LinkingTo: Rcpp, RcppArmadillo, RcppProgress, bsvars Suggests: knitr, tinytest Published: 2025-01-30 DOI: 10.32614/CRAN.package.bsvarSIGNs Author: Xiaolei Wang [aut, cre], Tomasz Woźniak [aut] Maintainer: Xiaolei Wang <adamwang15 at gmail.com> BugReports: https://github.com/bsvars/bsvarSIGNs/issues License: GPL (≥ 3) URL: https://bsvars.org/bsvarSIGNs/ NeedsCompilation: yes Citation: bsvarSIGNs citation info Materials: README, NEWS In views: Bayesian, TimeSeries CRAN checks: bsvarSIGNs results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=bsvarSIGNs to link to this page.
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