MSE.CGS.SMP: Mean square error (MSE).

In BSGS: Bayesian Sparse Group Selection

Description

Calculate the mean square error.

Usage

MSE.CGS.SMP(Output, Y, X)

Arguments

Output	A list of random samples for parameters generated by CGS or SMP algorithm.
Y	Observations.
X	Design matrix.

Value

Reture the mean square error.

Examples

## Not run: 
output = BSGS.Simple(Y, X, Group.Index, r.value, eta.value, beta.value, tau2.value, 
		 rho.value, theta.value, sigma2.value, nu, lambda, Num.of.Iter.Inside.CompWise, 
		 Num.Of.Iteration, MCSE.Sigma2.Given)
MSE.CGS.SMP(output, Y, X)

## End(Not run)

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