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bayesianVARs  

MCMC Estimation of Bayesian Vectorautoregressions
View on CRAN: Click here


Download and install bayesianVARs package within the R console
Install from CRAN:
install.packages("bayesianVARs")

Install from Github:
library("remotes")
install_github("cran/bayesianVARs")

Install by package version:
library("remotes")
install_version("bayesianVARs", "0.1.5")



Attach the package and use:
library("bayesianVARs")
Maintained by
Luis Gruber
[Scholar Profile | Author Map]
First Published: 2024-01-13
Latest Update: 2024-01-20
Description:
Efficient Markov Chain Monte Carlo (MCMC) algorithms for the fully Bayesian estimation of vectorautoregressions (VARs) featuring stochastic volatility (SV). Implements state-of-the-art shrinkage priors following Gruber & Kastner (2023) . Efficient equation-per-equation estimation following Kastner & Huber (2020) and Carrerio et al. (2021) .
How to cite:
Luis Gruber (2024). bayesianVARs: MCMC Estimation of Bayesian Vectorautoregressions. R package version 0.1.5, https://cran.r-project.org/web/packages/bayesianVARs. Accessed 07 Apr. 2025.
Previous versions and publish date:
0.1.0 (2024-01-13 18:00), 0.1.1 (2024-01-17 22:32), 0.1.2 (2024-01-20 14:52), 0.1.3 (2024-06-26 00:00), 0.1.4 (2024-09-06 17:00)
Other packages that cited bayesianVARs R package
View bayesianVARs citation profile
Other R packages that bayesianVARs depends, imports, suggests or enhances
Complete documentation for bayesianVARs
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