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>.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("mfbvar")

0.4.0 by Sebastian Ankargren, 8 months ago


https://github.com/ankargren/mfbvar


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