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
)a ts object which include all endogenous variables in VAR
a lag order in VAR
iterations of the MCMC
the first random draws discarded in MCMC
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.
the number of CPU cores in parallel computations.
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.