几何生成分布族:综述

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY
Teena Goyal, S. Maurya, S. Nadarajah
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引用次数: 0

摘要

本文对几何生成的分布族进行了回顾。在此分布族的基础上,提出了几种分布。该族可以通过将零截断几何分布与任何其他模型或分布族的复合概念来提出。在这里,我们提供了一个完整的调查,并列出了贡献的相关研究工作,他们的子模型,危险率,并利用了真实的数据集。我们还讨论了10个幂级数分布,60个基于几何分布族的分布。这些数字显示了几何分布族的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geometric generated family of distributions: A review
The present article represents a review of the geometric generated family of distributions. Based on this family of distribution, several distributions are proposed. The family can be proposed by using the compounding concept of zero truncated geometric distribution with any other model or family of distributions. Here, we provide a complete survey on this family of distributions and also listed the contributory related research work, their sub-models, hazard rates, and utilized real datasets. We also address 10 power series distributions, 60 distributions based on the geometric family of distribution. These numbers show the importance of the geometric family of distribution.
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来源期刊
CiteScore
1.60
自引率
10.00%
发文量
30
审稿时长
>12 weeks
期刊介绍: The Brazilian Journal of Probability and Statistics aims to publish high quality research papers in applied probability, applied statistics, computational statistics, mathematical statistics, probability theory and stochastic processes. More specifically, the following types of contributions will be considered: (i) Original articles dealing with methodological developments, comparison of competing techniques or their computational aspects. (ii) Original articles developing theoretical results. (iii) Articles that contain novel applications of existing methodologies to practical problems. For these papers the focus is in the importance and originality of the applied problem, as well as, applications of the best available methodologies to solve it. (iv) Survey articles containing a thorough coverage of topics of broad interest to probability and statistics. The journal will occasionally publish book reviews, invited papers and essays on the teaching of statistics.
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