Nonparametric estimation of conditional distributions

László Györfi, Michael Kohler

Research output: Article

15 Citations (Scopus)

Abstract

Estimation of conditional distributions is considered. It is assumed that the conditional distribution is either discrete or that it has a density with respect to the Lebesgue measure. Partitioning estimates of the conditional distribution are constructed and results concerning consistency and rate of convergence of the integrated total variation error of the estimates are presented.

Original languageEnglish
Pages (from-to)1872-1879
Number of pages8
JournalIEEE Transactions on Information Theory
Volume53
Issue number5
DOIs
Publication statusPublished - máj. 1 2007

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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