Modeling tropical tuna shifts: An inflated power logit regression approach

• Published in: Biometrical Journal
• Main Authors: Queiroz, Francisco F., Ferrari, Silvia L. P.
• Other Authors: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2024
• Subjects: North Atlantic
• Online Access: http://dx.doi.org/10.1002/bimj.202300288; https://onlinelibrary.wiley.com/doi/pdf/10.1002/bimj.202300288

Abstract 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.