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Fast Resampling Weighted v-Statistics
Chunxiao Zhou · jiseong Park · Yun Fu

Tue Dec 04 10:22 AM -- 10:26 AM (PST) @ Harveys Convention Center Floor, CC

In this paper, a novel, computationally fast, and alternative algorithm for com- puting weighted v-statistics in resampling both univariate and multivariate data is proposed. To avoid any real resampling, we have linked this problem with finite group action and converted it into a problem of orbit enumeration. For further computational cost reduction, an efficient method is developed to list all orbits by their symmetry order and calculate all index function orbit sums and data function orbit sums recursively. The computational complexity analysis shows reduction in the computational cost from n! or nn level to low-order polynomial level.

Author Information

Chunxiao Zhou (NIH (National Institutes of Health))
jiseong Park
Yun Fu (Northeastern University)

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