sim_ssvs_var {bvhar}

Generate SSVS Parameters

Description

This function generates parameters of VAR with SSVS prior.

Usage

sim_ssvs_var(
  bayes_spec,
  p,
  dim_data = NULL,
  include_mean = TRUE,
  minnesota = FALSE,
  mn_prob = 1,
  method = c("eigen", "chol")
)

sim_ssvs_vhar(
  bayes_spec,
  har = c(5, 22),
  dim_data = NULL,
  include_mean = TRUE,
  minnesota = c("no", "short", "longrun"),
  mn_prob = 1,
  method = c("eigen", "chol")
)

Arguments

bayes_spec

A SSVS model specification by set_ssvs().

p

VAR lag

dim_data

Specify the dimension of the data if hyperparameters of bayes_spec have constant values.

include_mean

Add constant term (Default: TRUE) or not (FALSE)

minnesota

Only use off-diagonal terms of each coefficient matrices for restriction. In sim_ssvs_var() function, use TRUE or FALSE (default). In sim_ssvs_vhar() function, "no" (default), "short" type, or "longrun" type.

mn_prob

Probability for own-lags.

method

Method to compute \Sigma^{1/2}.

har

Numeric vector for weekly and monthly order. By default, c(5, 22).

Value

List including coefficients.

VAR(p) with SSVS prior

Let \alpha be the vectorized coefficient of VAR(p).

(\alpha \mid \gamma)

(\gamma_i)

(\eta_j \mid \omega_j)

(\omega_{ij})

(\psi_{ii}^2)

VHAR with SSVS prior

Let \phi be the vectorized coefficient of VHAR.

(\phi \mid \gamma)

(\gamma_i)

(\eta_j \mid \omega_j)

(\omega_{ij})

(\psi_{ii}^2)

References

George, E. I., & McCulloch, R. E. (1993). Variable Selection via Gibbs Sampling. Journal of the American Statistical Association, 88(423), 881–889.

George, E. I., Sun, D., & Ni, S. (2008). Bayesian stochastic search for VAR model restrictions. Journal of Econometrics, 142(1), 553–580.

Ghosh, S., Khare, K., & Michailidis, G. (2018). High-Dimensional Posterior Consistency in Bayesian Vector Autoregressive Models. Journal of the American Statistical Association, 114(526).

Koop, G., & Korobilis, D. (2009). Bayesian Multivariate Time Series Methods for Empirical Macroeconomics. Foundations and Trends® in Econometrics, 3(4), 267–358.