1. The data | 2. The model | 3. The identification of Uhlig (2005) | 4. The responses | 5. Comparison with bsvarSIGNs | 6. The joint acceptance method | References
Package: acpbvar 0.2.0
Federica Ursillo
acpbvar: Bayesian Structural VARs with Asymmetric Conjugate Priors
Implements Bayesian estimation of structural Vector Autoregressions in the asymmetric A-form of Chan (2022) <doi:10.3982/QE1381>, with an asymmetric Minnesota prior whose own-lag and cross-lag hyperparameters are selected by empirical Bayes via the closed-form marginal likelihood. Exact equation-by-equation posterior simulation in the structural form (independent Normal-Inverse-Gamma draws) provides posterior draws of the reduced-form parameters; structural identification through sign restrictions follows the algorithm of Rubio-Ramirez, Waggoner and Zha (2010) <doi:10.1111/j.1467-937X.2009.00578.x>. Impulse responses, posterior bands, and acceptance diagnostics are computed from the accepted draws.
Authors:
acpbvar_0.2.0.tar.gz
acpbvar_0.2.0.zip(r-4.7-any)acpbvar_0.2.0.zip(r-4.6-any)acpbvar_0.2.0.zip(r-4.5-any)
acpbvar_0.2.0.tgz(r-4.6-any)acpbvar_0.2.0.tgz(r-4.5-any)
acpbvar_0.2.0.tar.gz(r-4.7-any)acpbvar_0.2.0.tar.gz(r-4.6-any)
acpbvar_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
acpbvar/json (API)
| # Install 'acpbvar' in R: |
| install.packages('acpbvar', repos = c('https://ursillofederica.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ursillofederica/acpbvar/issues
bayesianimpulse-responsemacroeconometricssign-restrictionssvar
Last updated from:7359263e05. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 121 | ||
| source / vignettes | OK | 190 | ||
| linux-release | OK | 146 | ||
| macos-release | OK | 141 | ||
| macos-oldrel | OK | 164 | ||
| windows-devel | OK | 83 | ||
| windows-release | OK | 81 | ||
| windows-oldrel | OK | 109 | ||
| wasm-release | OK | 95 |
Exports:build_s2build_yXcollect_irfscompute_irfoptim_hyperplot_irfspost_simrecover_rfsign_restrictsimulate_var_example
Dependencies:
acpbvar on real data: the monetary policy shock of Uhlig (2005)
Last update: 2026-10-17
Started: 2026-10-12
acpbvar: a complete workflow
1. A structural VAR with a known sign pattern | 2. Equation-by-equation preparation | 3. Empirical Bayes hyperparameter selection | 4. Posterior simulation | 5. Structural identification through sign restrictions | Partial identification | Restrictions beyond impact | Two ways of accepting a draw | Reading the diagnostics | 6. Impulse responses | Extracting the responses | 7. Recovery of the true impact | 8. Common mistakes | References
Last update: 2026-10-11
Started: 2026-10-08
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Print, summary and plot methods for acpbvar objects | acpbvar-methods plot.acpbvar_irf print.acpbvar_irf print.acpbvar_post print.acpbvar_signs print.summary.acpbvar_irf summary.acpbvar_irf |
| Estimate residual variances from univariate AR fits | build_s2 |
| Build response and regressor matrices for the A-form VAR | build_yX |
| Collect impulse responses across accepted draws | collect_irfs |
| Compute structural impulse responses for a single draw | compute_irf |
| Empirical Bayes selection of Minnesota prior tightness | optim_hyper |
| Plot posterior impulse responses with credible bands | plot_irfs |
| Posterior simulation for the asymmetric A-form BVAR | post_sim |
| Recover reduced-form quantities from a structural A-form draw | recover_rf |
| Structural identification via sign restrictions (RRWZ algorithm) | sign_restrict |
| Simulate a small structural VAR with known sign restrictions | simulate_var_example |