基于排序的零增强模型的高效回归分析

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-05-14 DOI:10.1007/s00180-024-01503-3

Deborah Kanda, Jingjing Yin, Xinyan Zhang, Hani Samawi

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引用次数: 0

摘要

有几种零增量模型可用于涉及大量零结果的估计。零膨胀回归模型和阶跃回归模型是处理计数终点的两种模型。在本文中，我们将极端排序集抽样（ERSS）方案应用于零膨胀和阶跃回归模型的估计中。我们提供的理论推导表明，与使用这些零膨胀模型的简单随机抽样（SRS）相比，ERSS 更具优势。我们还进行了模拟研究，比较了 ERSS 与 SRS 的效率，最后，我们用真实数据集说明了应用情况。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Efficient regression analyses with zero-augmented models based on ranking

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Efficient regression analyses with zero-augmented models based on ranking

Several zero-augmented models exist for estimation involving outcomes with large numbers of zero. Two of such models for handling count endpoints are zero-inflated and hurdle regression models. In this article, we apply the extreme ranked set sampling (ERSS) scheme in estimation using zero-inflated and hurdle regression models. We provide theoretical derivations showing superiority of ERSS compared to simple random sampling (SRS) using these zero-augmented models. A simulation study is also conducted to compare the efficiency of ERSS to SRS and lastly, we illustrate applications with real data sets.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.