If a linear regression model is used for prediction, the mean squared error of prediction (MSEP) measures the performance of the model. The MSEP is a function of unknown parameters and good estimates ...

Different estimates of the mean squared error of prediction for linear regression models are derived by the bootstrap and cross-validation approaches. A comparison is made under normal error ...

Residual plots can be used to validate assumptions about the regression model.