English

On Rates Attainable under Random Design: A Negative Answer to a Problem of Robins

Statistics Theory 2026-07-14 v1

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>1s>1 and integer d>4sd>4s, when the regression function is ss-H\"older, 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 nβn^{-\beta} with β=d(3s+1)+8s(d+2s)(d+4)\beta=\frac{d(3s+1)+8s}{(d+2s)(d+4)}. Hence the conjectured rate n4s/(d+4s)n^{-4s/(d+4s)} is not uniformly attainable.

Keywords

Cite

@article{arxiv.2607.13170,
  title  = {On Rates Attainable under Random Design: A Negative Answer to a Problem of Robins},
  author = {P. M. Aronow and Patrick Lopatto},
  journal= {arXiv preprint arXiv:2607.13170},
  year   = {2026}
}

Comments

54 pages