On the choice of nonparametric entropy estimator in entropy-based goodness-of-fit test statistics

Sangun Park, Dong Wan Shin

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Entropy-based goodness-of-fit test statistics can be established by estimating the entropy difference or Kullback-Leibler information, and several entropy-based test statistics based on various entropy estimators have been proposed. In this article, we first give comments on some problems resulting from not satisfying the moment constraints. We then study the choice of the entropy estimator by noting the reason why a test based on a better entropy estimator does not necessarily provide better powers.

Original languageEnglish
Pages (from-to)809-819
Number of pages11
JournalCommunications in Statistics - Theory and Methods
Volume41
Issue number5
DOIs
StatePublished - 2012

Keywords

  • Goodness-of-fit test
  • Kullback-Leibler information
  • Maximum entropy
  • Order statistics
  • Sample entropy

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