  The Wilcoxon-Mann-Whitney test is a robust competitor of the t-test in the
univariate setting. For finite dimensional multivariate data, several
extensions of the Wilcoxon-Mann-Whitney test have been shown to have better
performance than Hotelling's $T^{2}$ test for many non-Gaussian distributions
of the data. In this paper, we study a Wilcoxon-Mann-Whitney type test based on
spatial ranks for data in infinite dimensional spaces. We demonstrate the
performance of this test using some real and simulated datasets. We also
investigate the asymptotic properties of the proposed test and compare the test
with a wide range of competing tests.
