bvar: Bayesian Vector Autoregression

In mboeck11/BTSM: Bayesian Time Series Models

Bayesian Vector Autoregression

Description

Bayesian Vector Autoregression

Bayesian Vector Autoregression

Usage

bpvar(Data, plag=1,draws=5000,burnin=5000,prior="NG",SV=TRUE,h=0,thin=1,
             hyperpara=NULL,eigen=FALSE,
             Ex=NULL,cons=FALSE,trend=FALSE,applyfun=NULL,cores=NULL,verbose=TRUE)

bvar(Data, plag=1,draws=5000,burnin=5000,prior="NG",SV=TRUE,h=0,thin=1,
             hyperpara=NULL,eigen=FALSE,
            Ex=NULL,cons=FALSE,trend=FALSE,applyfun=NULL,cores=NULL,verbose=TRUE)

Arguments

Data	Data in matrix form
plag	number of lags
draws	number of saved draws.
burnin	number of burn-ins.
prior	which prior
SV	If set to TRUE stochastic volatility is enabled.
h	holdout-sample.
thin	thinning factor
hyperpara	hyperparameter set
eigen	should eigenvalues be computed?
Ex	exogenous variables to add to the model
cons	If set to TRUE a constant is included.
trend	If set to TRUE a trend is included.
applyfun	parallelization
cores	number of cores
verbose	verbosity option

mboeck11/BTSM documentation built on Oct. 9, 2022, 9:14 p.m.