library(Matching)
library(snow)
source("AutoCluster3.R")

data(lalonde)
attach(lalonde)

     #The covariates we want to match on
X = cbind(age, educ, black, hisp, married, nodegr, u74, u75, re75, re74)

     #The covariates we want to obtain balance on
BalanceMat <- cbind(age, educ, black, hisp, married, nodegr, u74, u75, re75, re74,
                    I(re74*re75))

     #
     #Let's call GenMatch() to find the optimal weight to give each
     #covariate in 'X' so as we have achieved balance on the covariates in
     #'BalanceMat'. This is only an example so we want GenMatch to be quick
     #so the population size has been set to be only 16 via the 'pop.size'
     #option. This is *WAY* too small for actual problems.
     #For details see http://sekhon.berkeley.edu/papers/MatchingJSS.pdf.
     #

cl <- NCPUS()
genout <- GenMatch(Tr=treat, X=X, BalanceMatrix=BalanceMat, estimand="ATE", M=1,
                   pop.size=16, max.generations=10, wait.generations=1,
                   cluster=cl)
stopCluster(cl)