mfbvar: 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) <doi:10.1080/07350015.2014.954707>, or the steady-state prior, as advocated by Ankargren, Unosson and Yang (2018) <http://uu.diva-portal.org/smash/get/diva2:1260262/FULLTEXT01.pdf>.

Getting started

Package details

AuthorSebastian Ankargren [cre, aut] (<https://orcid.org/0000-0003-4415-8734>), Yukai Yang [aut]
MaintainerSebastian Ankargren <[email protected]>
LicenseGPL-3
Version0.4.0
URL https://github.com/ankargren/mfbvar
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("mfbvar")

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mfbvar documentation built on Dec. 28, 2018, 1:04 a.m.