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:Fabian Krueger

bvarsv_1.1.1.tar.gz
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bvarsv_1.1.1.tgz(r-4.6-x86_64)bvarsv_1.1.1.tgz(r-4.6-arm64)bvarsv_1.1.1.tgz(r-4.5-x86_64)bvarsv_1.1.1.tgz(r-4.5-arm64)
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bvarsv_1.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
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

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

usmacro - US Macroeconomic Time Series
usmacro.update - US Macroeconomic Time Series

On CRAN:

openblas cpp

5.57 score 32 stars 1 packages 77 scripts 671 downloads 6 exports 2 dependencies

Last updated from:7b601e6857. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	156
linux-devel-x86_64	OK	114
source / vignettes	OK	187
linux-release-arm64	OK	154
linux-release-x86_64	OK	142
macos-release-arm64	OK	209
macos-release-x86_64	OK	257
macos-oldrel-arm64	OK	177
macos-oldrel-x86_64	OK	422
windows-devel	OK	136
windows-release	OK	111
windows-oldrel	OK	90
wasm-release	OK	111

Exports:bvar.sv.tvp impulse.responses parameter.draws predictive.density predictive.draws sim.var1.sv.tvp

Dependencies:Rcpp RcppArmadillo

Citation

Development and contributors

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