bvar_conj_simulate: Simulate from conjugate N-IW posterior distribution
In bdemeshev/bvarr: Package for Bayesian Vector Auto Regressions

Description Usage Arguments Details Value Examples

Simulate from conjugate N-IW posterior distribution

1 2	bvar_conj_simulate(v_post, Omega_post_root, S_post, Phi_post, verbose = FALSE, keep = 10)

`v_post`	posterior nu, scalar
`Omega_post_root`	[k x k] 'root' of Omega posterior matrix
`S_post`	[m x m] posterior scale matrix for noise covariance
`Phi_post`	[k x m] posterior expected values for coefs
`verbose`	TRUE will show some debugging messages, FALSE by default
`keep`	number of simulations

Simulate from conjugate N-IW posterior distribution

coda object with simulations

data(Yraw)
dummy <- bvar_conj_lambda2dummy(Yraw, p = 2)
hyper <- bvar_conj_dummy2hyper(dummy$Y_cniw, dummy$X_cniw)
# these are priors but just for testing let's pretend that they are posteriors
post_sample <- bvar_conj_simulate(v_post = 10,
hyper$Omega_root, hyper$S, hyper$Phi)