Modeling tropical tuna shifts: An inflated power logit regression approach

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 tun...

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Bibliographic Details
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
Description
Summary: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.

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