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.
- Version1.0.5
- R version≥ 3.3.0
- LicenseGPL-3
- LicenseLICENSE
- Needs compilation?No
- BVAR citation info
- Last release02/16/2024
Documentation
Team
Nikolas Kuschnig
Lukas Vashold
Show author detailsRolesAuthorNirai Tomass
Show author detailsRolesContributorMichael McCracken
Show author detailsRolesdtcSerena Ng
Show author detailsRolesdtc
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- Imports1 package
- Suggests3 packages
- Reverse Depends1 package