ssvs_prior {bvartools} | R Documentation |
Stochastic Search Variable Selection Prior
Description
Calculates the priors for a Bayesian VAR model, which employs stochastic search variable selection (SSVS).
Usage
ssvs_prior(object, tau = c(0.05, 10), semiautomatic = NULL)
Arguments
object |
an object of class |
tau |
a numeric vector of two elements containing the prior standard errors of restricted
variables ( |
semiautomatic |
an optional numeric vector of two elements containing the factors by which
the standard errors associated with an unconstrained least squares estimate of the VAR model are
multiplied to obtain the prior standard errors of restricted ( |
Value
A list containing the vectors of prior standard deviations for restricted and unrestricted variables, respectively.
References
George, E. I., Sun, D., & Ni, S. (2008). Bayesian stochastic search for VAR model restrictions. Journal of Econometrics, 142(1), 553–580. doi:10.1016/j.jeconom.2007.08.017
Examples
# Prepare data
data("e1")
data <- diff(log(e1))
# Generate model input
object <- gen_var(data)
# Obtain SSVS prior
prior <- ssvs_prior(object, semiautomatic = c(.1, 10))