BVAR (1.0.0)

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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.

Maintainer: Nikolas Kuschnig
Author(s): Nikolas Kuschnig [aut, cre] (<>), Lukas Vashold [aut], Michael McCracken [dtc], Serena Ng [dtc]

License: GPL-3 | file LICENSE

Uses: mvtnorm, coda, vars, tinytest

Released 22 days ago.

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