ML Anthology

On the Asymptotic Normality of an Estimate of a Regression Functional

László Györfi, Harro Walk
JMLR 2015 pp. 1863-1877
/jmlr/2015/gyorfi2015jmlr-asymptotic/

Abstract

An estimate of the second moment of the regression function is introduced. Its asymptotic normality is proved such that the asymptotic variance depends neither on the dimension of the observation vector, nor on the smoothness properties of the regression function. The asymptotic variance is given explicitly.

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Text

Györfi and Walk. "On the Asymptotic Normality of an Estimate of a Regression Functional." Journal of Machine Learning Research, 2015.

Markdown

[Györfi and Walk. "On the Asymptotic Normality of an Estimate of a Regression Functional." Journal of Machine Learning Research, 2015.](https://mlanthology.org/jmlr/2015/gyorfi2015jmlr-asymptotic/)

BibTeX

@article{gyorfi2015jmlr-asymptotic,
  title     = {{On the Asymptotic Normality of an Estimate of a Regression Functional}},
  author    = {Györfi, László and Walk, Harro},
  journal   = {Journal of Machine Learning Research},
  year      = {2015},
  pages     = {1863-1877},
  volume    = {16},
  url       = {https://mlanthology.org/jmlr/2015/gyorfi2015jmlr-asymptotic/}
}