Strong universal consistent estimate of the minimum mean squared error

Luc Devroye, Paola G. Ferrario, László Györfi, Harro Walk

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

Consider the regression problem with a response variable Y and a feature vector X. For the regression function m(x)= E{Y ∣ X=x}, we introduce new and simple estimators of the minimum mean squared error L*=E{(Y — m(X))2}, and prove their strong consistencies. We bound the rate of convergence, too.

Original languageEnglish
Title of host publicationEmpirical Inference
Subtitle of host publicationFestschrift in Honor of Vladimir N. Vapnik
PublisherSpringer Berlin Heidelberg
Pages143-160
Number of pages18
ISBN (Electronic)9783642411366
ISBN (Print)9783642411359
DOIs
Publication statusPublished - Jan 1 2013

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Devroye, L., Ferrario, P. G., Györfi, L., & Walk, H. (2013). Strong universal consistent estimate of the minimum mean squared error. In Empirical Inference: Festschrift in Honor of Vladimir N. Vapnik (pp. 143-160). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-41136-6_14