Hierarchical Bayesian Vector Autoregression

Estimation of hierarchical Bayesian vector autoregressive models. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015) . Functions to compute and identify impulse responses, calculate forecasts, forecast error variance decompositions and scenarios are available. Several methods to print, plot and summarise results facilitate analysis.


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Reference manual

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install.packages("BVAR")

1.0.1 by Nikolas Kuschnig, 8 months ago


https://github.com/nk027/bvar


Report a bug at https://github.com/nk027/bvar/issues


Browse source code at https://github.com/cran/BVAR


Authors: Nikolas Kuschnig [aut, cre] , Lukas Vashold [aut] , Michael McCracken [dtc] , Serena Ng [dtc]


Documentation:   PDF Manual  


Task views: Time Series Analysis, Bayesian Inference


GPL-3 | file LICENSE license


Imports mvtnorm, stats, graphics, utils, grDevices

Suggests coda, vars, tinytest


Depended on by BVARverse.


See at CRAN