Bracketing numbers of convex and m-monotone functions on polytopes

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Abstract

We study bracketing covering numbers for spaces of bounded convex functions in the Lp norms. Bracketing numbers are crucial quantities for understanding asymptotic behavior for many statistical nonparametric estimators. Bracketing number upper bounds in the supremum distance are known for bounded classes that also have a fixed Lipschitz constraint. However, in most settings of interest, the classes that arise do not include Lipschitz constraints, and so standard techniques based on known bracketing numbers cannot be used. In this paper, we find upper bounds for bracketing numbers of classes of convex functions without Lipschitz constraints on arbitrary polytopes. Our results are of particular interest in many multidimensional estimation problems based on convexity shape constraints. Additionally, we show other applications of our proof methods; in particular we define a new class of multivariate functions, the so-called m-monotone functions. Such functions have been considered mathematically and statistically in the univariate case but never in the multivariate case. We show how our proof for convex bracketing upper bounds also applies to the m-monotone case.

Original languageEnglish (US)
Article number105425
JournalJournal of Approximation Theory
Volume256
DOIs
StatePublished - Aug 2020

Bibliographical note

Funding Information:
Supported by National Science Foundation grant DMS-1712664.

Publisher Copyright:
© 2020 Elsevier Inc.

Keywords

  • Bracketing entropy
  • Convergence rates
  • Convex functions
  • Convex polytope
  • Covering numbers
  • Kolmogorov metric entropy
  • Nonparametric estimation

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