BVAR {FAVAR}

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 \beta, and vb0 is the prior of the variance of \beta. nu0 is the degree of freedom of Wishart distribution for \Sigma^{-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.