Hierarchical Bayesian Vector Autoregression

Estimation of hierarchical Bayesian vector autoregressive models following Kuschnig & Vashold (2021) . 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.


Reference manual

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1.0.2 by Nikolas Kuschnig, 2 months ago


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