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[Deprecated] This function generates parameters of VAR with Horseshoe prior.

Usage

sim_horseshoe_var(
  p,
  dim_data = NULL,
  include_mean = TRUE,
  minnesota = FALSE,
  method = c("eigen", "chol")
)

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

Arguments

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_horseshoe_var() function, use TRUE or FALSE (default). In sim_horseshoe_vhar() function, no (default), short type, or longrun type.

method

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

har

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