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Large Deviation Results for the Nonparametric Regression Function Estimator on Functional Data

Statistics Theory 2016-11-25 v1 Methodology Statistics Theory

Abstract

This paper is devoted to the study of large deviation behaviors in the setting of the estimation of the regression function on functional data. A large deviation principle is stated for a process Zn, defined below, allowing to derive a pointwise large deviation principle for the Nadaraya-Watson-type l-indexed regression function estimator as a by-product. Moreover, a uniform over VC-classes Cherno? type large deviation result is stated for the deviation of the l-indexed regression estimator.

Keywords

Cite

@article{arxiv.1111.5989,
  title  = {Large Deviation Results for the Nonparametric Regression Function Estimator on Functional Data},
  author = {Djamal Louani and Sidi Mohamed Ould Maouloud},
  journal= {arXiv preprint arXiv:1111.5989},
  year   = {2016}
}

Comments

23 pages

R2 v1 2026-06-21T19:41:32.716Z