sim_mnvhar_coef: Generate Minnesota BVAR Parameters

In bvhar: Bayesian Vector Heterogeneous Autoregressive Modeling

Generate Minnesota BVAR Parameters

Description

This function generates parameters of BVAR with Minnesota prior.

Usage

sim_mnvhar_coef(bayes_spec = set_bvhar(), full = TRUE)

Arguments

bayes_spec	A BVHAR model specification by set_bvhar() (default) or set_weight_bvhar().
full	Generate variance matrix from IW (default: TRUE) or not (FALSE)?

Details

Normal-IW family for vector HAR model:

\Phi \mid \Sigma_e \sim MN(M_0, \Omega_0, \Sigma_e)

\Sigma_e \sim IW(\Psi_0, \nu_0)

Value

List with the following component.

coefficients

BVHAR coefficient (MN)

covmat

BVHAR variance (IW or diagonal matrix of sigma of bayes_spec)

References

Kim, Y. G., and Baek, C. (2024). Bayesian vector heterogeneous autoregressive modeling. Journal of Statistical Computation and Simulation, 94(6), 1139-1157.

See Also

• set_bvhar() to specify the hyperparameters of VAR-type Minnesota prior.

• set_weight_bvhar() to specify the hyperparameters of HAR-type Minnesota prior.

Examples

# Generate (Phi, Sigma)
# BVHAR-S
# sigma: 1, 1, 1
# lambda: .1
# delta: .1, .1, .1
# epsilon: 1e-04
set.seed(1)
sim_mnvhar_coef(
  bayes_spec = set_bvhar(
    sigma = rep(1, 3),
    lambda = .1,
    delta = rep(.1, 3),
    eps = 1e-04
  ),
  full = TRUE
)

bvhar documentation built on April 4, 2025, 5:22 a.m.