The Continuous Bernoulli Distribution: Mathematical Characterization, Fractile Regression, Computational Simulations, and Applications

Mustafa Korkmaz, Víctor Leiva, Carlos Martin-Barreiro

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The continuous Bernoulli distribution is defined on the unit interval and has a unique property related to fractiles. A fractile is a position on a probability density function where the corresponding surface is a fixed proportion. This article presents the derivation of properties of the continuous Bernoulli distribution and formulates a fractile or quantile regression model for a unit response using the exponentiated continuous Bernoulli distribution. Monte Carlo simulation studies evaluate the performance of point and interval estimators for both the continuous Bernoulli distribution and the fractile regression model. Real-world datasets from science and education are analyzed to illustrate the modeling abilities of the continuous Bernoulli distribution and the exponentiated continuous Bernoulli quantile regression model.

Original languageEnglish
Article number386
JournalFractal and Fractional
Volume7
Issue number5
DOIs
StatePublished - May 2023

Keywords

  • Bernoulli distribution
  • R software
  • likelihood and Monte Carlo methods
  • point estimation
  • quantile function
  • residual analysis

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