Revstat Statistical Journal (Jul 2022)

Modeling Heavy-Tailed Bounded Data by the Trapezoidal Beta Distribution with Applications

  • Jorge Figueroa-Zúñiga ,
  • Sebastián Niklitschek-Soto ,
  • Víctor Leiva ,
  • Shuangzhe Liu

DOI
https://doi.org/10.57805/revstat.v20i3.380
Journal volume & issue
Vol. 20, no. 3

Abstract

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In this paper, by using a new method, we derive the trapezoidal beta (TB) distribution and its properties. The TB distribution is a mixture model, generalizes both the beta and rectangular beta distributions, and allows one to describe bounded data with heavy right and/or left tails. In relation to the two-parameter beta distribution, we add two additional parameters which have an intuitive interpretation. The four TB parameters are estimated with the expectation-maximization algorithm. We conduct a simulation study to evaluate performance of the TB distribution. An application with real data is carried out, which includes a comparison among the beta, rectangular beta and TB distributions indicating that the TB one describes these data better.

Keywords