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.

翻译：块最大值方法是时间序列极值分析中经典且广泛应用的统计方法。近期研究发现，相较于使用不相交块最大值，采用滑动块最大值可改进那些渐近性质由经验均值驱动的估计量。本文将此结论推广至多元时间序列情形下任意阶的一般非退化U-统计量。针对特定实例给出了详细推导：经验方差、概率加权矩估计量和肯德尔tau统计量。此外，研究结果被拓展至底层样本为分段平稳的情形。通过蒙特卡洛模拟研究验证了有限样本性质。