  The block maxima method is a classical and widely applied statistical method
for time series extremes. It has recently been found that respective estimators
whose asymptotics are driven by empirical means can be improved by using
sliding rather than disjoint block maxima. Similar results are derived for
general non-degenerate U-statistics of arbitrary order, in the multivariate
time series case. Details are worked out for selected examples: the empirical
variance, the probability weighted moment estimator and Kendall's tau
statistic. The results are also extended to the case where the underlying
sample is piecewise stationary. The finite-sample properties are illustrated by
a Monte Carlo simulation study.
