基于不确定性的非参数中位数检验对冠状病毒患者的分析

IF 0.1 Q4 STATISTICS & PROBABILITY
Muhammad Aslam, Muhammad Saleem
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引用次数: 0

摘要

达克沃斯检验是著名的非参数统计检验。用于比较两个总体的中位数。然而,基于经典统计学的传统达克沃斯检验在处理来自嗜中性粒细胞群体的数据时是不充分的。本文提出了达克沃斯测试的修改版本,专门为中性粒细胞统计设计。这种新颖的方法使Duckworth测试应用于不精确、不确定或不确定间隔记录的数据。介绍了在嗜中性统计下提出的检验统计量,并将其应用于实际的Covid-19数据。通过综合分析和仿真研究,证明了所提出的中性粒细胞统计下的Duckworth检验的有效性优于现有的经典统计下的Duckworth检验。收稿日期:2023年8月7日。收稿日期:2023年9月25日
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ANALYSIS OF CORONA PATIENTS USING UNCERTAINTY-BASED NON-PARAMETRIC MEDIAN TEST
Duckworth’s test is a well-known non-parametric statistical test  used for comparing the medians of two populations. However, the conventional Duckworth’s test, based on classical statistics, is inadequate when dealing with data originating from neutrosophic populations. This paper presents a modified version of Duckworth’s test, specifically designed for neutrosophic statistics. This novel approach enables the application of Duckworth’s test to imprecise, uncertain, or data recorded in indeterminate intervals. The proposed test statistic under neutrosophic statistics is introduced and applied to real-world Covid-19 data. Through comprehensive analysis and simulation studies, the efficacy of the proposed Duckworth’s test under neutrosophic statistics is demonstrated to surpass that of the existing Duckworth’s test under classical statistics. Received: August 7, 2023Accepted: September 25, 2023
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来源期刊
JP Journal of Biostatistics
JP Journal of Biostatistics STATISTICS & PROBABILITY-
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