Smoothing parameter selection for power optimality in testing of regression curves

We consider selection of smoothing parameters to obtain optimal power in tests of regression curves. We examine three tests and propose empirical smoothing parameters to maximize the power in each test. We also show that the data-based smoothing parameters converge to the optimal smoothing parameters as sample sizes gel larger. We conduct a simulation study for various classes of alternative showing the effectiveness of the proposed procedures.