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Revista Colombiana de Estadística
versão impressa ISSN 0120-1751
Rev.Colomb.Estad. vol.46 no.1 Bogotá jan./jun. 2023 Epub 18-Jan-2023
https://doi.org/10.15446/rce.v46n1.101517
ARTÍCULOS ORIGINALES DE INVESTIGACIÓN
Robust Circular Logistic Regression Model and Its Application to Life and Social Sciences
Modelo de regresión logística circular robusto y su aplicación a las ciencias de la vida y sociales
1Department of Applied Mathematics, Materials Science and Engineering and Electronic Technology, Rey Juan Carlos University, Madrid, Spain
This paper presents robust estimators for binary and multinomial circular logistic regression, where a circular predictor is related to the response. An extensive Monte Carlo Simulation Study clearly shows the robustness of proposed methods. Finally, three numerical examples of Botany, Crime and Meteorology illustrate the application of these methods to Life and Social Sciences. Although in the Botany data the proposed method showed little improvement, in the Crime and Meteorological data an increment up to 5% and 4% of accuracy, respectively, is achieved.
Key words: Circular data; Circular logistic regression; Maximum likelihood estimation; Multinomial circular logistic regression; Robustness
Este artículo presenta estimadores robustos para el modelo de regresión logística circular binomial y mutinomial. Un estudio de Monte Cario muestra la robustez de los métodos propuestos. Finalmente, tres ejemplos numéricos en botánica, criminalística y meteorología muestran la aplicación de estos modelos a las Ciencias.
Palabras clave: Datos circulares; Regresión logística circular; Regresión logística circular multinomial; Estimación de máxima verosimilitud; Ro bustez
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Received: April 2022; Accepted: November 2022
This is an open-access article distributed under the terms of the Creative Commons Attribution License
