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

Abstract

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.
Original languageEnglish
Pages (from-to)1-19
Number of pages19
JournalRevstat Statistical Journal
Publication statusE-pub ahead of print - 2020

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