Estimate bvar conjugate model from setup

Estimate bvar conjugate model from setup

bvar_conj_estimate(setup, keep = 2000, verbose = FALSE)

Arguments

setup	list containing: X [T x k] Y [T x m] X_plus [T_plus x k] Y_plus [T_plus x m] v_prior p number of lags
keep	the number of simulations. If keep is zero only posterior hyperparameters are calculated
verbose	TRUE will show some debugging messages, FALSE by default

Value

model list containing X, Y, X_plus, Y_plus, p, v_prior, sample (if keep>0) Omega_post, v_post, S_post, Phi_post

Details

Estimate bvar conjugate model from setup

Examples

data(Yraw)
setup <- bvar_conj_setup(Yraw, p = 4, lambda = c(0.2, 1, 1, 1, 100, 100))
#> Calculation of hyperparameters from lambdas is not implemented yet :(
#> You may safely ignore the message if you supply lambdas :)
model <- bvar_conj_estimate(setup, keep = 10)