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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.5 |
rolling linux/jammy R-4.5 | BVAR_1.0.5.tar.gz |
1.1 MiB |
1.0.5 |
rolling linux/noble R-4.5 | BVAR_1.0.5.tar.gz |
1.1 MiB |
1.0.5 |
rolling source/ R- | BVAR_1.0.5.tar.gz |
843.2 KiB |
1.0.5 |
latest linux/jammy R-4.5 | BVAR_1.0.5.tar.gz |
1.1 MiB |
1.0.5 |
latest linux/noble R-4.5 | BVAR_1.0.5.tar.gz |
1.1 MiB |
1.0.5 |
latest source/ R- | BVAR_1.0.5.tar.gz |
843.2 KiB |
1.0.5 |
2026-04-26 source/ R- | BVAR_1.0.5.tar.gz |
843.2 KiB |
1.0.5 |
2026-04-23 source/ R- | BVAR_1.0.5.tar.gz |
843.2 KiB |
1.0.5 |
2026-04-09 windows/windows R-4.5 | BVAR_1.0.5.zip |
1.1 MiB |
1.0.5 |
2025-04-20 source/ R- | BVAR_1.0.5.tar.gz |
843.2 KiB |