BVAR_linear {BGVAR} | R Documentation |
This is the sub function that estimates the country VAR models. It is directly called from gvar.ssvs
.
BVAR_linear(nr, gW = gW, xglobal = xglobal, cN, p = 4, nsave = 500, nburn = 500, hyper = list(c_tau = 0.01, d_tau = 0.01, e_lambda = 1.5, d_lambda = 1, prmean = 0, a_start = 0.6, sample_A = TRUE), prior = "NG", thin = 0.1, sv = TRUE, trend = FALSE)
nr |
Is a selector referring to the number of the country model to be estimated (same order as in |
gW |
Is a list object of length N containing the country-specific weight matrices. |
xglobal |
is a matrix object of dimension T times N (T # of observations, K # of variables in the system). |
cN |
Character vector of the country names. |
p |
Number of lags used (the same for domestic, exogenous and weakly exogenous variables). |
nsave |
Number of draws saved. |
nburn |
Number of burn-ins. |
hyper |
Is a list object that defines the hyperparameters of the chosen prior. See |
prior |
Either "SSVS", "SIMS" or "NG". See the description for |
thin |
Is a thinning interval which grabs save_thin percent of your posterior output. As a rule of thumb, workspaces get large if save_thin*saves>500. |
sv |
Set to |
trend |
Set to |
Florian Huber
Part of the algorithm is based on Koop and Korobilis.
See also bgvar
.