BVAR: Hierarchical Bayesian Vector Autoregression

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.

Package details

AuthorNikolas Kuschnig [aut, cre] (<https://orcid.org/0000-0002-6642-2543>), Lukas Vashold [aut] (<https://orcid.org/0000-0002-3562-3414>), Nirai Tomass [ctb], Michael McCracken [dtc], Serena Ng [dtc]
MaintainerNikolas Kuschnig <nikolas.kuschnig@wu.ac.at>
LicenseGPL-3 | file LICENSE
Version1.0.5
URL https://github.com/nk027/bvar
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("BVAR")

Try the BVAR package in your browser

Any scripts or data that you put into this service are public.

BVAR documentation built on May 29, 2024, 5:34 a.m.