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

Jorge I. Figueroa-Zu'Niga , Sebastian Niklitschek-Soto, Víctor Leiva, Shuangzhe Liu

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


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 rectangu-lar 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, rectan-gular beta and TB distributions indicating that the TB one describes these data better.

Original languageEnglish
Pages (from-to)387-404
Number of pages18
JournalRevstat Statistical Journal
Issue number3
Publication statusPublished - 2022


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