print.bgvar.CD

<p>object of class <code>bgvar.CD</code>.</p>

Estimation of Bayesian Global Vector Autoregressions (BGVAR) with different prior setups and the possibility to introduce stochastic volatility. Built-in priors include the Minnesota, the stochastic search variable selection and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391 <doi:10.1002/jae.2504>. Post-processing functions allow for doing predictions, structurally identify the model with short-run or sign-restrictions and compute impulse response functions, historical decompositions and forecast error variance decompositions. Plotting functions are also available.

Maximilian Boeck

BGVAR

Bayesian Global Vector Autoregressions

Martin Feldkircher

Florian Huber

Christopher Sims

print.bgvar.CD function

Print convergence diagnostics — print.bgvar.CD

Print convergence diagnostics

print.bgvar.CD: Print convergence diagnostics

Description

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