BVAR function

Bayesian Estimation of VAR

Estimate a VAR base on Bayesian method

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.

Returns

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.