lasso.dr1<-function(x,y,kfold=5,rep=10,plot=T,grid=seq(from=0,to=1,length=100)){
# wrapper for lasso in lars, with modifications to cv.lars
require(lars)
# set.seed(seed)
ok<-complete.cases(x,y)
x<-x[ok,]                            # get rid of na's
y<-y[ok]                             # since regsubsets can't handle na's
m<-ncol(x)
n<-nrow(x)
as.matrix(x)->x
cvout<-cv.lars1(x,y,K=kfold,plot.it=F,fraction=grid)
sumcv<-cvout$cv
frac<-cvout$fraction
if(rep >1){
for(i in 1:(rep-1)){
sumcv<-sumcv+cv.lars1(x,y,K=kfold,plot.it=F,fraction=grid)$cv
}   # ends for
}   # ends if
sumcv<-sumcv/rep
if(plot) plot(frac,sumcv)
sfrac<-frac[which.min(sumcv)]       # assume frac stays the same
object<-lars(x,y,type="lasso")
fit <- predict.lars(object,x,s=sfrac,type="fit",mode="fraction")$fit
coeff<-predict.lars(object,x,s=sfrac,type="coef",mode="fraction")$coefficients
st<-sum(coeff !=0)                                          # number nonzero
mse<-sum((y-fit)^2)/(n-st-1)
colnames(x)<-colnames(x,do.NULL=F,prefix="")      # corrects for no colnames
x<-x[,colnames(x)[which(coeff !=0)]]
cat("",fill=T)
cat("K (num. of folds)=",kfold,fill=T)
cat("Num. of reps)=",rep,fill=T)
cat("Fraction from CV=",sfrac,fill=T)
cat("number nonzero=",st,fill=T)
cat("mse=",mse,fill=T)
cat("Variables Selected =",colnames(x),fill=T)
return(list(l.object=object,frac=frac,fit=fit,coeff=coeff,st=st,mse=mse,sumcv=sumcv))
}