Cross-validation using the t statistic

One application area of regression analysis is simulation where the regression model may explain the relationship between the simulation model's inputs and outputs.However, whether or not the regression model is used in a simulation context, its validity can be tested by comparing the model's forecast to one or more new observations not used in the estimation of the model's parameters. The familiar Student or t statistic is proposed for this comparison, combined with a Bonferroni approach accounting for the presence of multiple, dependent validation observations.A ‘trick’ is used to obtain as many validation observations as possible. This trick is also known as cross-validation.Several Monte Carlo experiments are performed to study the α and β errors of the proposed validation procedure. The experimental results suggest that the procedure is worthwhile.