Nothing
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.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Nikolas 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] |
| Maintainer | Nikolas Kuschnig <nikolas.kuschnig@wu.ac.at> |
| License | GPL-3 | file LICENSE |
| Version | 1.0.5 |
| URL | https://github.com/nk027/bvar |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the BVAR package in your browser
Any scripts or data that you put into this service are public.
