This package includes three programs and two example data sets.
1) VarSelection.Linear.standard.R: An R program to perform variable selections in partially linear models with all conditional posterior distributions being standard. In case needed, a function EstRho() used to estimate rho, the scale parameter in the Gaussian kernel, is also included.
2) VarSelection.Linear.MH.R: An R program to perform variable selections in partially linear models by use of the Metropolis-Hastings algorithm. This program is robust against numerical singularity in the kernel matrix K, but it will be slower.
3) VarSelection.Probit.R: An R program to perform variable selections under the probit regression model. 
4) two example data sets: Linear.Example3.txt in the partially linear setting and Probit.Example3.txt in the probit regression setting. Both are for model 3 noted in the section of Simulation Studies. In total 12 candidate predictors and one covariate are considered. The truly important variables are the first three variables. 