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- W2947868604 abstract "In many hypothesis testing problems, the test statistics are degenerate U ‐statistics. One of the challenges in practice is the computation of U ‐statistics for large dataset. In this paper, we aim to reduce the computation complexity of degenerate U ‐statistics by using the divide‐and‐conquer method. Specifically, we partition the full n data points into k n even disjoint groups, compute the U ‐statistics on each group, and combine them by averaging. In this way, the running time is reduced to , where m is the order of the U ‐statistics. Besides, we study the optimal test rate of the divide‐and‐conquer methods. For degenerate U ‐statistics, the optimal rate is , the same as the optimal test rate for the nondegenerate case. The simulation and real data confirm that the proposed method has high power and faster running time." @default.
- W2947868604 created "2019-06-07" @default.
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- W2947868604 date "2019-01-01" @default.
- W2947868604 modified "2023-09-24" @default.
- W2947868604 title "Distributed inference for degenerate U ‐statistics" @default.
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- W2947868604 doi "https://doi.org/10.1002/sta4.234" @default.
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