In this example, kernel selection methods for MMD based statistics are
illustrated. A difficult synthetic dataset is used to illustrate their
performance in two-sample testing. All kernel selection methods for MMD
work via creating a combined kernel with all desired baseline kernels.
The example demonstrates how to perform kernel selection and use it
for two-sample testing. Methods for both single and combined kernels
are demonstrated. In addition, type I and II error estimates
are computed. As usual, there are more iterations/samples required in
practice.
See tutorial and Class documentation for more details.
