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bayesianVARs

MCMC Estimation of Bayesian Vectorautoregressions

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 (2025) <doi:10.1016/j.ijforecast.2025.02.001>. Efficient equation-per-equation estimation following Kastner & Huber (2020) <doi:10.1002/for.2680> and Carrerio et al. (2021) <doi:10.1016/j.jeconom.2021.11.010>.

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VersionRepositoryFileSize
0.1.8 rolling linux/jammy R-4.5 bayesianVARs_0.1.8.tar.gz 1.1 MiB
0.1.8 rolling linux/noble R-4.5 bayesianVARs_0.1.8.tar.gz 1.1 MiB
0.1.8 rolling source/ R- bayesianVARs_0.1.8.tar.gz 771.3 KiB
0.1.8 latest linux/noble R-4.5 bayesianVARs_0.1.8.tar.gz 1.1 MiB
0.1.8 latest source/ R- bayesianVARs_0.1.8.tar.gz 771.3 KiB
0.1.8 latest linux/jammy R-4.5 bayesianVARs_0.1.8.tar.gz 1.1 MiB
0.1.8 2026-04-26 source/ R- bayesianVARs_0.1.8.tar.gz 771.3 KiB
0.1.8 2026-04-23 source/ R- bayesianVARs_0.1.8.tar.gz 771.3 KiB
0.1.8 2026-04-09 windows/windows R-4.5 bayesianVARs_0.1.8.zip 1.4 MiB
0.1.5 2025-04-20 source/ R- bayesianVARs_0.1.5.tar.gz 314.9 KiB

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