get.wprior: Mixing weight estimation.
In icmm: Empirical Bayes Variable Selection via ICM/M Algorithm

Description Usage Arguments Details Value Author(s) Examples

Given other parameters, this function estimates a mixing weight from the mode of its full conditional distribution function.

1	get.wprior(beta)

beta

a (p*1) matrix of regression coefficients.

Given other parameters, this function estimates a mixing weight from the mode of its full conditional distribution function. This function is called when use the independent prior of predictors (no prior on structured predictors).

Return a scalar value of a mixing weight.

Vitara Pungpapong, Min Zhang, Dabao Zhang

data(simGaussian)
Y<-as.matrix(simGaussian[,1])
X<-as.matrix(simGaussian[,-1])
# Obtain initial values from lasso
data(initbetaGaussian)
beta<-as.matrix(initbetaGaussian)
# Estimate the mixing weight
w<-get.wprior(beta)