An upper bound on the probability of misclassification in terms of Matusita's measure of affinity

Binay K. Bhattacharya, Godfried T. Toussaint

Research output: Contribution to journalArticle

Abstract

A distribution-free upper bound is derived on the Bayes probability of misclassification in terms of Matusita's measure of affinity among several distributions for the M-hypothesis discrimination problem. It is shown that the bound is as sharp as possible.

Original languageEnglish (US)
Pages (from-to)161-165
Number of pages5
JournalAnnals of the Institute of Statistical Mathematics
Volume34
Issue number1
DOIs
StatePublished - Dec 1 1982

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Keywords

  • 3.36
  • 3.63
  • 5.25
  • 5.30
  • 5.5
  • Bhattacharyya coefficient
  • Matusita's measure of affinity
  • Probability of misclassification
  • decision theory
  • discrimination rules
  • information measures
  • pattern classification

ASJC Scopus subject areas

  • Statistics and Probability

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