泊松区域偏倚的Ailamujia分布及其在环境和医学中的应用

Q4 Mathematics

Statistics in Transition Pub Date : 2022-09-01 DOI:10.2478/stattrans-2022-0036

Ahmad Aijaz, S. Q. Ain, Ahmad Afaq, Rajnee Tripathi

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引用次数: 0

摘要

摘要本文建立了一个新的泊松区域偏置的Ailamujia分布来分析计数数据。它是通过使用复合技术将泊松分布和面积偏倚的Ailamujia分布结合而成的。研究了公式分布的几种分布性质。确定并明确表达了其老化特性。用各种图表来说明概率质量函数(pmf)和累积分布函数(cdf)的特征。采用极大似然估计方法对模型的参数进行估计。最后，使用两个数据集来验证所研究分布的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Poisson area-biased Ailamujia Distribution and its applications in environmental and medical sciences

Abstract In this paper, a new Poisson area-biased Ailamujia distribution has been formulated to analyse count data. It was created by combining two distributions: the Poisson and area-biased Ailamujia distributions, using the compounding technique. Several distributional properties of the formulated distribution were studied. Its ageing characteristics were determined and expressed explicitly. A variety of diagrams were used to demonstrate the characteristics of the probability mass function (pmf) and the cumulative distribution function (cdf). The parameter of the developed model was estimated by employing the maximum likelihood estimation approach. Finally, two data sets were used to demonstrate the effectiveness of the investigated distribution.

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来源期刊

Statistics in Transition Decision Sciences-Statistics, Probability and Uncertainty

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

9 weeks

期刊介绍： Statistics in Transition (SiT) is an international journal published jointly by the Polish Statistical Association (PTS) and the Central Statistical Office of Poland (CSO/GUS), which sponsors this publication. Launched in 1993, it was issued twice a year until 2006; since then it appears - under a slightly changed title, Statistics in Transition new series - three times a year; and after 2013 as a regular quarterly journal." The journal provides a forum for exchange of ideas and experience amongst members of international community of statisticians, data producers and users, including researchers, teachers, policy makers and the general public. Its initially dominating focus on statistical issues pertinent to transition from centrally planned to a market-oriented economy has gradually been extended to embracing statistical problems related to development and modernization of the system of public (official) statistics, in general.