Beta-normal distribution and its applications

Nicholas Eugene, Carl Lee, Felix Famoye

Research output: Contribution to journalArticlepeer-review

625 Scopus citations

Abstract

This paper introduces a general class of distributions generated from the logit of the beta random variable. A special case of this family is the beta-normal distribution. The shape properties of the beta-normal distribution are discussed. Estimation of parameters of the beta-normal distribution by the maximum likelihood method is also discussed. The beta-normal distribution provides great flexibility in modeling not only symmetric heavy-tailed distributions, but also skewed and bimodal distributions. The flexibility of this distribution is illustrated by applying it to two empirical data sets and comparing the results to previously used methods.

Original languageEnglish
Pages (from-to)497-512
Number of pages16
JournalCommunications in Statistics - Theory and Methods
Volume31
Issue number4
DOIs
StatePublished - Apr 2002

Keywords

  • Bimodality
  • Estimation
  • Moments
  • Order statistics
  • Skewness
  • Symmetry

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