Mixed-Frequency Bayesian VAR Models

Estimation of mixed-frequency Bayesian vector autoregressive (VAR) models with Minnesota or steady-state priors. The package implements a state space-based VAR model that handles mixed frequencies of the data. The model is estimated using Markov Chain Monte Carlo to numerically approximate the posterior distribution, where the prior can be either the Minnesota prior, as used by Schorfheide and Song (2015) , or the steady-state prior, as advocated by Ankargren, Unosson and Yang (2018) < http://uu.diva-portal.org/smash/get/diva2:1260262/FULLTEXT01.pdf>.


Reference manual

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0.4.0 by Sebastian Ankargren, 8 months ago


Report a bug at https://github.com/ankargren/mfbvar/issues

Browse source code at https://github.com/cran/mfbvar

Authors: Sebastian Ankargren [cre, aut] , Yukai Yang [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports Rcpp, ggplot2, methods, pbapply, utils

Suggests testthat, covr

Linking to Rcpp, RcppArmadillo

See at CRAN