A New Class of Probability Distributions via Half-Elliptical Functions

In this paper, we develop a new family of distributions supported on a bounded interval with a probability density function that is constructed from two elliptical arcs. The distribution can take on a variety of shapes and has three basic parameters: minimum, maximum, and mode. Compared to classical bounded distributions such as the beta and triangular distributions, the proposed semi-elliptical family offers greater flexibility in capturing diverse shapes of distributions, in symmetric and asymmetric settings. Its construction from elliptical arcs enables smoother transitions and more natural tail behaviors, making it suitable for applications where classical models may exhibit rigidity or over-simplicity. We give general expression for the density and distribution function of the new distribution. Properties of this distribution are studied and parameter estimation is discussed. Monte Carlo simulation results show the performance of our estimators under many sets of situations. Furthermore, we show the advantages of our distribution over the commonly used triangular distribution in approximating beta distributions.

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Publication Details

Journal
Mathematics
Published
2025-05-29
DOI
https://doi.org/10.3390/math13111811
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

A New Class of Probability Distributions via Half-Elliptical Functions

Lukun Zheng, Ngoc Nhi Nguyen, Peyton Erslan
Mathematics
Statistical Distribution Estimation and Applications
article

A New Class of Probability Distributions via Half-Elliptical Functions

Lukun Zheng, Ngoc Nhi Nguyen, Peyton Erslan
article en

Abstract

In this paper, we develop a new family of distributions supported on a bounded interval with a probability density function that is constructed from two elliptical arcs. The distribution can take on a variety of shapes and has three basic parameters: minimum, maximum, and mode. Compared to classical bounded distributions such as the beta and triangular distributions, the proposed semi-elliptical family offers greater flexibility in capturing diverse shapes of distributions, in symmetric and asymmetric settings. Its construction from elliptical arcs enables smoother transitions and more natural tail behaviors, making it suitable for applications where classical models may exhibit rigidity or over-simplicity. We give general expression for the density and distribution function of the new distribution. Properties of this distribution are studied and parameter estimation is discussed. Monte Carlo simulation results show the performance of our estimators under many sets of situations. Furthermore, we show the advantages of our distribution over the commonly used triangular distribution in approximating beta distributions.

MathematicsVol. 13(11)
Western Kentucky University (US)
Openalex Percentile: Top 88%
Statistical Distribution Estimation and Applications
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A New Class of Probability Distributions via Half-Elliptical Functions — Lukun Zheng, Ngoc Nhi Nguyen, et al. · Mathematics (2025) | TGRS Research Map | TGRS