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BVAR (version 0.2.0)

Hierarchical Bayesian Vector Autoregression

Description

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.

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Install

install.packages('BVAR')

Monthly Downloads

1,457

Version

0.2.0

License

GPL-3 | file LICENSE

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Repository

https://github.com/nk027/bvar

Maintainer

Nikolas Kuschnig

Last Published

September 5th, 2019

Functions in BVAR (0.2.0)

Log-Likelihood method for Bayesian VARs

Retrieve companion matrix from a Bayesian VAR

Coefficient and VCOV methods for Bayesian VARs

FRED-QD: Quarterly Database for Macroeconomic Research

Impulse response and forecast error methods for Bayesian VARs

Summary method for Bayesian VARs

Hyperparameter trace & density plot

Plotting method for Bayesian VAR impulse responses

plot.bvar_fcast

Plotting method for Bayesian VAR forecasts

Density methods for Bayesian VARs

Fitted and residual methods for Bayesian VARs

Predict method for Bayesian VARs

Plotting method for Bayesian VARs

Method for coda Markov chain Monte Carlo objects

Minnesota prior settings

Hierarchical Bayesian Vector Autoregression

Metropolis-Hastings settings

Impulse response settings

Dummy prior settings

Forecast settings