Higher order normalizing transformations of asymptotic U-statistics for removing bias, skewness and kurtosis

Yumi Fujioka, Yoshihiko Maesono

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

This paper proposes a normalizing transformation which removes bias, skewness and kurtosis, simultaneously. Its convergence rate to the standard normal distribution is o(n-1). The transformation is polynomial and monotone. We consider a class of asymptotic U-statistics, which includes most of interesting statistics.

Original languageEnglish
Pages (from-to)47-74
Number of pages28
JournalJournal of Statistical Planning and Inference
Volume83
Issue number1
DOIs
Publication statusPublished - Jan 1 2000

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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