Bashir Shakila, Masood Bushra, Sanaullah Aamir, Al-Essa Laila A
Department of Statistics, Forman Christian College (A Chartered University), Lahore, Pakistan.
Department of Statistics, COMSATS University Islamabad, Lahore Campus, Pakistan.
Heliyon. 2024 Nov 19;11(2):e40487. doi: 10.1016/j.heliyon.2024.e40487. eCollection 2025 Jan 30.
Circular distributions within the radians range describe two-dimensional directions by mapping points onto a unit circle. These distributions are vital in diverse fields such as medicine, ecology, and environmental studies, where measurements are expressed in terms of angles. However, when these distributions involve measuring angles within the radians range, they constitute axial or semi-circular data instead of circular data. This research seeks to introduce the semi-circular Marshall-Olkin extended Burr-XII distribution tailored for semi-circle datasets. Objectives encompass presenting its fundamental characteristics and applications. The inverse stereographic projection technique is applied for its development, deriving characteristics like trigonometric moments, mode, hazard function, and survival function. Five estimation techniques assess the distribution's parameters. Monte Carlo simulations evaluate parameter estimation methods for different sample sizes. Modeling the semi-circular Marshall-Olkin extended Burr-XII distribution with real-life semi-circle data of posterior corneal curvature of eye demonstrates its adaptability. Comparisons with existing distributions affirm its effectiveness. Extending to the -axial model produces the Stereographic--axial Marshall-Olkin extended Burr-XII distribution, offering a distinct probability density function (pdf). This transformation gives rise to specific scenarios and new models. The proposed semi-circular Marshall-Olkin extended Burr-XII distribution proves adept at handling real-world semi-circular data. The extension to the -axial model and subsequent transformations introduces innovative models, demonstrated by superior compatibility in both circular and semi-circular datasets.
弧度范围内的圆形分布通过将点映射到单位圆上来描述二维方向。这些分布在医学、生态学和环境研究等不同领域至关重要,在这些领域中测量值以角度表示。然而,当这些分布涉及测量弧度范围内的角度时,它们构成轴向或半圆形数据而非圆形数据。本研究旨在引入为半圆形数据集量身定制的半圆形马歇尔 - 奥尔金扩展伯尔 - XII 分布。目标包括呈现其基本特征和应用。其开发应用了逆立体投影技术,得出诸如三角矩、众数、风险函数和生存函数等特征。五种估计技术用于评估该分布的参数。蒙特卡罗模拟针对不同样本量评估参数估计方法。用眼睛后角膜曲率的实际生活半圆形数据对半圆形马歇尔 - 奥尔金扩展伯尔 - XII 分布进行建模,证明了其适应性。与现有分布的比较证实了其有效性。扩展到 - 轴模型产生立体 - - 轴马歇尔 - 奥尔金扩展伯尔 - XII 分布,提供了独特的概率密度函数(pdf)。这种变换产生了特定场景和新模型。所提出的半圆形马歇尔 - 奥尔金扩展伯尔 - XII 分布证明擅长处理现实世界的半圆形数据。向 - 轴模型的扩展及后续变换引入了创新模型,在圆形和半圆形数据集中均表现出卓越的兼容性。