热带金枪鱼转移建模：膨胀幂对数回归法

IF 1.3 3区生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Biometrical Journal Pub Date : 2024-05-03 DOI:10.1002/bimj.202300288

Francisco F. Queiroz, Silvia L. P. Ferrari

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引用次数: 0

摘要

我们介绍了一类新的零或一膨胀幂对数（IPL）回归模型，它是分析有边界连续数据和边界观测数据的多功能工具。这些模型被用于探索气候变化对北大西洋热带金枪鱼分布的影响。研究结果表明，我们的建模方法足以处理数据中的异常值。在诊断分析和推断稳健性方面，它都表现出优于竞争对手模型的性能。我们为 IPL 回归模型在实际应用中的拟合提供了一种用户友好型方法。

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Modeling tropical tuna shifts: An inflated power logit regression approach

We introduce a new class of zero-or-one inflated power logit (IPL) regression models, which serve as a versatile tool for analyzing bounded continuous data with observations at a boundary. These models are applied to explore the effects of climate changes on the distribution of tropical tuna within the North Atlantic Ocean. Our findings suggest that our modeling approach is adequate and capable of handling the outliers in the data. It exhibited superior performance compared to rival models in both diagnostic analysis and regarding the inference robustness. We offer a user-friendly method for fitting IPL regression models in practical applications.

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来源期刊

Biometrical Journal 生物-数学与计算生物学

CiteScore

3.20

自引率

5.90%

发文量

119

审稿时长

6-12 weeks

期刊介绍： Biometrical Journal publishes papers on statistical methods and their applications in life sciences including medicine, environmental sciences and agriculture. Methodological developments should be motivated by an interesting and relevant problem from these areas. Ideally the manuscript should include a description of the problem and a section detailing the application of the new methodology to the problem. Case studies, review articles and letters to the editors are also welcome. Papers containing only extensive mathematical theory are not suitable for publication in Biometrical Journal.