BVAR (0.2.1)

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Hierarchical Bayesian Vector Autoregression.

Toolkit for the estimation of hierarchical Bayesian vector autoregressions. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015) . Allows for the computation of impulse responses and forecasts and provides several methods for assessing results.

Maintainer: Nikolas Kuschnig
Author(s): Nikolas Kuschnig [aut, cre], Lukas Vashold [aut], Michael McCracken [dtc] (author of the FRED-QD dataset)

License: GPL-3 | file LICENSE

Uses: mvtnorm, coda, vars

Released about 1 month ago.

3 previous versions



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