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On Rates Attainable under Random Design: A Negative Answer to a Problem of Robins
arXiv Math
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이 매체는 공공·자유 라이선스로 본문을 직접 표시합니다.Abstract
We give a negative answer to a problem posed by James Robins on estimating a constant conditional variance in nonparametric regression under random design.
For every $s>1$ and integer $d>4s$, when the regression function is $s$-Hölder, the unknown design density is bounded above and away from zero, and the conditional error laws may depend on the design but have mean zero, a common variance, and uniformly bounded fourth moments, we show that the minimax root-mean-square risk is bounded below by $n^{-\beta}$ with $\beta=\frac{d(3s+1)+8s}{(d+2s)(d+4)}$.
Hence the conjectured rate $n^{-4s/(d+4s)}$ is not uniformly attainable.
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