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半圆形改良 III 型布氏分布,应用不同的估计方法。

Half circular modified burr-III distribution, application with different estimation methods.

机构信息

National College of Business Administration and Economics, Lahore, Pakistan.

University of Veterinary and Animal Sciences, Lahore, Pakistan.

出版信息

PLoS One. 2022 May 17;17(5):e0261901. doi: 10.1371/journal.pone.0261901. eCollection 2022.

Abstract

The data related to many medical, environmental and ecological variables are often measured in terms of angles wherein its range is defined in [0,π). This type of data is referred to as axial or half circular data. Modeling based on half circular data has not received its due share of attention in statistical literature. In this paper, we introduce a new half circular distribution based on inverse stereographic projection technique on modified Burr-III distribution, called the half circular modified Burr-III (hcMB-III) distribution. The basic properties of the proposed distribution are derived. It is common observation that while estimating the parameters of a model, one usually adopts maximum likelihood estimation method as the starting point. In this paper, we consider seven frequentist methods of estimation, besides using maximum likelihood method for estimating the parameters of the hcMB-III distribution. Monte Carlo simulations are performed for investigating the performances of the considered methods in terms of their biases and mean square errors using small, medium and large sample sizes. Finally, one data set related to posterior corneal curvature of the eyes of 23 patients, is analyzed to check potentiality of the newly proposed model.

摘要

许多医学、环境和生态变量的数据通常以角度来测量,其范围定义在 [0,π) 内。这种类型的数据被称为轴向或半圆形数据。基于半圆形数据的建模在统计文献中并没有得到应有的重视。在本文中,我们引入了一种基于修正 Burr-III 分布的逆立体投影技术的新的半圆形分布,称为半圆形修正 Burr-III(hcMB-III)分布。推导了所提出分布的基本性质。在估计模型的参数时,人们通常采用最大似然估计方法作为起点,这是常见的观察结果。在本文中,我们考虑了七种频率方法的估计,除了使用最大似然方法来估计 hcMB-III 分布的参数。通过小、中、大样本量的蒙特卡罗模拟,研究了所考虑方法在偏差和均方误差方面的性能。最后,分析了与 23 名患者眼睛后角膜曲率相关的一组数据,以检查新提出的模型的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2393/9113593/49ef7b72da7d/pone.0261901.g001.jpg

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