pared to the KS test is that is does
not assume a continuous distribution. In [1]_, the authors conclude
that the test also has a higher power than the KS test in many
examples. They recommend the use of the ES test for discrete samples as
well as continuous samples with at least 25 observations each, whereas
`anderson_ksamp` is recommended for smaller sample sizes in the
continuous case.

The p-value is computed from the asymptotic distribution of the test
statistic which follows a `chi2` distribution. If the sample size of both
`x` and `y` is below 25, the small sample correction proposed in [1]_ is
applied to the test statistic.

The default values of `t` are determined in [1]_ by considering
various distributions and finding good values that lead to a high power
of the test in general. Table III in [1]_ gives the optimal values for
the distributions tested in that study. The values of `t` are scaled by
the semi-interquartile range in the implementation, see [1]_.

References
----------
.. [1] T. W. Epps and K. J. Singleton, "An omnibus test for the two-sample
   problem using the empirical characteristic function", Journal of
   Statistical Computation and Simulation 26, p. 177--203, 1986.

.. [2] S. J. Goerg and J. Kaiser, "Nonparametric testing of distributions
   - the Epps-Singleton two-sample test using the empirical characteristic
   function", The Stata Journal 9(3), p. 454--465, 2009.

