R: Sample version of group-wise Gibbs sampler for sparse group...
BSGS.Sample
R Documentation
Sample version of group-wise Gibbs sampler for sparse group selection.
Description
Generate the posterior samples by an approximation sampling method to perform Bayesian sparse group selection to identify the important groups of variables and variables within those.
Specify the group label to which the variable belongs.
r.value
Initial values of indicator variables for individual variables.
eta.value
Initial values of indicator variables for the group variables.
beta.value
Initial values of regression coefficients, β.
tau2.value
Variance in the prior distribution for regression coefficients.
rho.value
Prior inclusion probability for a variable.
theta.value
Prior inclusion probability for a group.
sigma2.value
Initial value of σ^2.
nu
The hyperparameter in the prior distribution of σ^2.
lambda
The hyperparameter in the prior distribution of σ^2.
Num.of.Iter.Inside.CompWise
Specify the number of iterations within component wise Gibbs sampler for variable selection within a group.
Num.Of.Iteration
Specify the number of iterations for sparse group variable selection.
MCSE.Sigma2.Given
Prespecified value which is used to stop simulating samples. When the MCSE of estimate of σ^2 less than the given value, the simulation is terminated.
Value
A list is returned with posterior random samples of regression coefficients, β, binary variables for group selection, η, binary variables for variable selection, γ, variance, σ^2 and the number of iterations performed and the elapsed time in second required for the run.