Dear all, I am trying to iterate an elastic net regression method on a matrix 1) Each column of the matrix ( nxp) will act as a response (y) and rest of the variables (columns) which means p-1 will act as predictor set 2) i want to store selected variables as matrix I wrote a code. Please help me to automate this procedure # install packages for analysis rm(list = ls()) library(caret) library(glmnet) X<-matrix(rnorm(100*500),nrow=100) y<-X[,1] # I want automatically it will take next column as a response means untill 500 columns X1<-X[,-1] # If I use first column as a response it should delete first column from the matrix dim(X1) ### Applicarion of the Elastic net for selecting the genes con<-trainControl(method="cv",number=10) fit_data<-train(X1, y,method="glmnet",metric="RMSE",trControl=con,tuneLength = 10) glmnetcalc<-glmnet(X1,y,alpha=fit_data$finalModel$tuneValue$.alpha) fitcoef<-predict(glmnetcalc,s=fit_data$finalModel$tuneValue$.alpha,type="coefficients") CoefEN_1<-as.matrix(fitcoef) write.table(CoefEN_1, "varSelect_1.txt") # I want to store the non zero values in a matrix thanks Nico [[alternative HTML version deleted]]