A family of skew-normal distributions for modeling proportions and rates with zeros/ones excess

Guillermo Martínez-Flórez, VICTOR ELISEO LEIVA SANCHEZ, Emilio Gómez-Déniz, Carolina Marchant

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper, we consider skew-normal distributions for constructing new a distribution which allows us to model proportions and rates with zero/one inflation as an alternative to the inflated beta distributions. The new distribution is a mixture between a Bernoulli distribution for explaining the zero/one excess and a censored skew-normal distribution for the continuous variable. The maximum likelihood method is used for parameter estimation. Observed and expected Fisher information matrices are derived to conduct likelihood-based inference in this new type skew-normal distribution. Given the flexibility of the new distributions, we are able to show, in real data scenarios, the good performance of our proposal.

Original languageEnglish
Article number1439
JournalSymmetry
Volume12
Issue number9
DOIs
StatePublished - Sep 2020
Externally publishedYes

Keywords

  • Beta distribution
  • Centered skew-normal distribution
  • Maximum-likelihood methods
  • Monte Carlo simulations
  • Proportions
  • R software
  • Rates
  • Zero/one inflated data

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