Package: bvarsv 1.1.1
bvarsv: Bayesian Analysis of a Vector Autoregressive Model with Stochastic Volatility and Time-Varying Parameters
R/C++ implementation of the model proposed by Primiceri ("Time Varying Structural Vector Autoregressions and Monetary Policy", Review of Economic Studies, 2005), with functionality for computing posterior predictive distributions and impulse responses.
Authors:
bvarsv_1.1.1.tar.gz
bvarsv_1.1.1.zip(r-4.5)bvarsv_1.1.1.zip(r-4.4)bvarsv_1.1.1.zip(r-4.3)
bvarsv_1.1.1.tgz(r-4.4-x86_64)bvarsv_1.1.1.tgz(r-4.4-arm64)bvarsv_1.1.1.tgz(r-4.3-x86_64)bvarsv_1.1.1.tgz(r-4.3-arm64)
bvarsv_1.1.1.tar.gz(r-4.5-noble)bvarsv_1.1.1.tar.gz(r-4.4-noble)
bvarsv_1.1.1.tgz(r-4.4-emscripten)bvarsv_1.1.1.tgz(r-4.3-emscripten)
bvarsv.pdf |bvarsv.html✨
bvarsv/json (API)
| # Install 'bvarsv' in R: |
| install.packages('bvarsv', repos = c('https://fk83.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/fk83/bvarsv/issues
- usmacro - US Macroeconomic Time Series
- usmacro.update - US Macroeconomic Time Series
Last updated 3 months agofrom:7b601e6857. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 04 2024 |
| R-4.5-win-x86_64 | OK | Nov 04 2024 |
| R-4.5-linux-x86_64 | OK | Nov 04 2024 |
| R-4.4-win-x86_64 | OK | Nov 04 2024 |
| R-4.4-mac-x86_64 | OK | Nov 04 2024 |
| R-4.4-mac-aarch64 | OK | Nov 04 2024 |
| R-4.3-win-x86_64 | OK | Nov 04 2024 |
| R-4.3-mac-x86_64 | OK | Nov 04 2024 |
| R-4.3-mac-aarch64 | OK | Nov 04 2024 |
Exports:bvar.sv.tvpimpulse.responsesparameter.drawspredictive.densitypredictive.drawssim.var1.sv.tvp
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bayesian Analysis of a Vector Autoregressive Model with Stochastic Volatility and Time-Varying Parameters | bvar.sv.tvp |
| US Macroeconomic Time Series | usmacro usmacro.update |
| Helper Functions to Access BVAR Forecast Distributions and Parameter Draws | parameter.draws predictive.density predictive.draws |
| Compute Impulse Response Function from a Fitted Model | impulse.responses |
| Simulate from a VAR(1) with Stochastic Volatility and Time-Varying Parameters | sim.var1.sv.tvp |
