BVAR: Bayesian Estimation of VAR
In FAVAR: Bayesian Analysis of a FAVAR Model

BVAR	R Documentation

Bayesian Estimation of VAR

Description

Estimate a VAR base on Bayesian method

Usage

BVAR(
  data,
  plag = 2,
  iter = 10000,
  burnin = 5000,
  prior = list(b0 = 0, vb0 = 0, nu0 = 0, s0 = 0, mn = list(kappa0 = NULL, kappa1 =
    NULL)),
  ncores = 1
)

Arguments

`data`	a `ts` object which include all endogenous variables in VAR
`plag`	a lag order in VAR
`iter`	iterations of the MCMC
`burnin`	the first random draws discarded in MCMC
`prior`	a list whose elements is named. `b0` is the prior of mean of β, and `vb0` is the prior of the variance of β. `nu0` is the degree of freedom of Wishart distribution for Σ^{-1}, i.e., a shape parameter, and `s0^{-1}` is scale parameters for the Wishart distribution. `mn` sets the Minnesota prior. If `prior$mn$kappa0` is not `NULL`, `b0,vb0` is neglected.
`ncores`	the number of CPU cores in parallel computations.

Value

a list:

A, the samples drawn for the coefficients of VAR
sigma, the samples drawn for the variance-covariance of the coefficients of VAR
sumrlt, a list include varcoef, varse, q25, q975 which are means, standard errors, 0.25 quantiles and 0.975 quantiles of A.