get.sigma: Standard deviation estimation.
In icmm: Empirical Bayes Variable Selection via ICM/M Algorithm

Description Usage Arguments Details Value Author(s) Examples

This function estimates the standard deviation when family="gaussian". This function is for internal use called by the icmm function.

1	get.sigma(Y, X, beta, alpha)

`Y`	an (n*1) numeric matrix of responses.
`X`	an (n*p) numeric design matrix.
`beta`	a (p*1) matrix of regression coefficients.
`alpha`	a scalar value of hyperparmeter `alpha`.

Estimate standard deviation as the mode of its full conditional distribution function when specify family="gaussian". This function is for internal use called by the icmm function.

Return a scalar value of standard deviation.

Vitara Pungpapong, Min Zhang, Dabao Zhang

data(simGaussian)
Y<-as.matrix(simGaussian[,1])
X<-as.matrix(simGaussian[,-1])
alpha<-0.5
# Obtain initial values from lasso
data(initbetaGaussian)
beta<-as.matrix(initbetaGaussian)
# Obtain sigma
sigma<-get.sigma(Y=Y, X=X, beta=beta, alpha=alpha)