Resampling is usually used to find the best tuning parameters for a model. However, for some models, such as linear regression model, there is no tuning parameters. In this case, what can we get from resampling on them?
In particular, in R caret package, you can train a linear regression model by using cross validation control function. In this case, how is the coefficient estimated? On the whole training sample? If so, what extra information can we get from applying CV on linear regression models?