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对两个参数负二项式分布的置信区间和预测区间

Md Mahadi Hasan¹, K Krishnamoorthy¹

¹Department of Mathematics, University of Louisiana at Lafayette, Lafayette, LA, USA.

Journal of applied statistics

|September 13, 2024

概括

本研究为两参数负二项式分布引入了简单的置信区间 (CI) 和预测区间 (PI). 与现有的概率CI相比,这些新方法为中等样本大小提供了更高的准确性.

科学领域:

统计统计统计统计
可能性理论概率理论.
统计分布的统计分布

背景情况:

两参数负二项式分布经常用于各种领域,包括生物学和质量控制.
准确的置信区间 (CI) 和预测区间 (PI) 对于使用这种分布进行可靠的统计推理至关重要.
构建CI和PI的现有方法可能是计算密集的或对中等样本大小的准确性较低.

研究的目的:

开发和评估一个简单,准确的置信区间 (CI) 两个参数负二项式分布的平均值.
建议和评估预测区间 (PI) 的性能,以此分布的未来样本的平均值.
将拟议的方法与现有的基于概率的方法进行比较.

主要方法:

开发基于大样本的方法来构建平均值的CI.
拟议的信贷机构与传统的基于可能性的信贷机构的比较.
为未来的样本平均值制定和评估预测间隔 (PI).
将方法应用于现实世界的数据集,以实践示例.

主要成果:

拟议的CI在计算上比概率CI更简单.
新的信贷机构在适度样本大小方面表现优于概率信贷机构.
提出的预测间隔为未来的观测提供了可靠的准确性.
有关示例证实了开发方法的实际实用性和有效性.

结论:

建议的简单置信区间为现有的两参数负二项式分布方法提供了一个实用且准确的替代方案.
开发的预测间隔对于预测未来的样本平均值是有效的.
这些方法提高了负二项式分布后数据的统计分析能力.

关键词:

采用联合抽样方法的方法.最大的概率估计估计.过度分散的情况.鱼类分布鱼类分布预测间隔的时间评分方法评分方法

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