Package index

Package

The baymar package

baymar baymar-package

baymar: Bayesian Matrix Autoregressions

Prior specification

Prior settings for Bayesian models.

set_mar_minnesota() is.matmnspec() is.bmarspec() is.kappaspec() experimental

Minnesota Prior Specification

set_kappa()

Hyperprior for kappa of Minnesota prior

set_mar_horseshoe() is.mathsspec()

Horseshoe Prior Specification

set_mar_ssvs()

SSVS Prior Specification

set_matfactor() is.matfactorspec()

Factor prior specification

Bayesian modeling

Bayesian MAR and others.

mar_bayes()

Fitting Bayesian MAR

mdfm_bayes()

Fitting Bayesian Matrix DFM

Forecasting

predict(<marbayes>)

Forecasting MAR

predict(<mdfmbayes>)

Forecasting MDFM

forecast_roll(<marbayes>)

Pseudo out-of-sample Forecasting based on Rolling Window

forecast_roll(<mdfmbayes>)

Pseudo out-of-sample Forecasting for MDFM based on Rolling Window

forecast_expand(<marbayes>)

Pseudo out-of-sample Forecasting based on Expanding Window

forecast_expand(<mdfmbayes>)

Pseudo out-of-sample Forecasting for MDFM based on Expanding Window

Simulation and Random Generation

sim_mar()

Generate Matrix Time Series following MAR(p)

Data

chanqi2025

Dataset used by Chan and Qi (2025)