CRAN

mfbvar 0.4.0

Mixed-Frequency Bayesian VAR Models

Released Dec 27, 2018 by Sebastian Ankargren

This package cannot yet be used with Renjin it depends on other packages which are not available: ggplot2 3.1.0

Dependencies

ggplot2 3.1.0 Rcpp RcppArmadillo 0.9.200.5.0 pbapply 1.3-4

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) .

Source

R
C++

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