CGS.SMP.PE: Posterior estimates of parameters.

In BSGS: Bayesian Sparse Group Selection

Description

Calculate the posterior estimates of parameters based on the samples generated from the posterior distribution by the stochastic matching pursuit (SMP).

Usage

CGS.SMP.PE(CGS.SMP.Output)

Arguments

CGS.SMP.Output

A list of random samples for parameters

Value

A list is returned with estimates of regression coefficients, β, binary variables for variable selection, γ, and variance, σ^2.

Examples

## Not run: 
output = CompWiseGibbsSMP(Y, X, beta.value, r, tau2, rho, sigma2, nu, lambda, 
	num.of.inner.iter, num.of.iteration, MCSE.Sigma2.Given)
CGS.SMP.PE(output)

## End(Not run)

BSGS documentation built on May 2, 2019, 4:21 a.m.