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Super-polynomial accuracy of one dimensional randomized nets using the median-of-means (2111.12676v3)

Published 24 Nov 2021 in stat.CO, cs.NA, math.NA, math.ST, and stat.TH

Abstract: Let $f$ be analytic on $[0,1]$ with $|f{(k)}(1/2)|\leq A\alphakk!$ for some constant $A$ and $\alpha<2$. We show that the median estimate of $\mu=\int_01f(x)\,\mathrm{d}x$ under random linear scrambling with $n=2m$ points converges at the rate $O(n{-c\log(n)})$ for any $c< 3\log(2)/\pi2\approx 0.21$. We also get a super-polynomial convergence rate for the sample median of $2k-1$ random linearly scrambled estimates, when $k=\Omega(m)$. When $f$ has a $p$'th derivative that satisfies a $\lambda$-H\"older condition then the median-of-means has error $O( n{-(p+\lambda)+\epsilon})$ for any $\epsilon>0$, if $k\to\infty$ as $m\to\infty$.

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