Estimation of hierarchical Bayesian vector autoregressive models following Kuschnig & Vashold (2021) <doi:10.18637/jss.v100.i14>. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015) <doi:10.1162/REST_a_00483>. Functions to compute and identify impulse responses, calculate forecasts, forecast error variance decompositions and scenarios are available. Several methods to print, plot and summarise results facilitate analysis.
Version: 1.0.5 Depends: R (≥ 3.3.0) Imports: mvtnorm, stats, graphics, utils, grDevices Suggests: coda, vars, tinytest Published: 2024-02-16 DOI: 10.32614/CRAN.package.BVAR Author: Nikolas Kuschnig [aut, cre], Lukas Vashold [aut], Nirai Tomass [ctb], Michael McCracken [dtc], Serena Ng [dtc] Maintainer: Nikolas Kuschnig <nikolas.kuschnig at wu.ac.at> BugReports: https://github.com/nk027/bvar/issues License: GPL-3 | file LICENSE URL: https://github.com/nk027/bvar NeedsCompilation: no Citation: BVAR citation info Materials: README, NEWS In views: Bayesian, TimeSeries CRAN checks: BVAR results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=BVAR to link to this page.
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