title: Implementing Monte Carlo Cross Validation on linear regression in R
body: <p>I'm having a dataset of 90 stations with a variety of different covariates which I would like to take for prediction by using a step-wise forward multiple regression. Therefore I would like to use Monte Carlo Cross Validation to estimate the performance of my linear model by splitting into test- and training tests for many times. 
  How can I implement the MCCV in R to test my model for certain iterations? I found the package WilcoxCV which gives me the observation number for each iteration. I also found the CMA-package which doesn't helps me a lot so far. 
  I checked all threads about MCCV but didn't find the answer. </p>