Published

2023-01-01

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

DOI:

https://doi.org/10.15446/rce.v46n1.101517

Keywords:

Circular data, Circular logistic regression, Maximum likelihood estimation, Multinomial circular logistic regression, Robustness (en)
Datos circulares, Regresión logística circular, Regresión logística circular multinomial, Estimación de máxima verosimilitud, Robustez (es)

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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.

Este artículo presenta estimadores robustos para el modelo de regresión logística circular binomial y mutinomial. Un estudio de Monte Carlo 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.

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How to Cite

APA

Castilla, E. (2023). Robust Circular Logistic Regression Model and Its Application to Life and Social Sciences. Revista Colombiana de Estadística, 46(1), 45–62. https://doi.org/10.15446/rce.v46n1.101517

ACM

[1]
Castilla, E. 2023. Robust Circular Logistic Regression Model and Its Application to Life and Social Sciences. Revista Colombiana de Estadística. 46, 1 (Jan. 2023), 45–62. DOI:https://doi.org/10.15446/rce.v46n1.101517.

ACS

(1)
Castilla, E. Robust Circular Logistic Regression Model and Its Application to Life and Social Sciences. Rev. colomb. estad. 2023, 46, 45-62.

ABNT

CASTILLA, E. Robust Circular Logistic Regression Model and Its Application to Life and Social Sciences. Revista Colombiana de Estadística, [S. l.], v. 46, n. 1, p. 45–62, 2023. DOI: 10.15446/rce.v46n1.101517. Disponível em: https://revistas.unal.edu.co/index.php/estad/article/view/101517. Acesso em: 28 mar. 2025.

Chicago

Castilla, Elena. 2023. “Robust Circular Logistic Regression Model and Its Application to Life and Social Sciences”. Revista Colombiana De Estadística 46 (1):45-62. https://doi.org/10.15446/rce.v46n1.101517.

Harvard

Castilla, E. (2023) “Robust Circular Logistic Regression Model and Its Application to Life and Social Sciences”, Revista Colombiana de Estadística, 46(1), pp. 45–62. doi: 10.15446/rce.v46n1.101517.

IEEE

[1]
E. Castilla, “Robust Circular Logistic Regression Model and Its Application to Life and Social Sciences”, Rev. colomb. estad., vol. 46, no. 1, pp. 45–62, Jan. 2023.

MLA

Castilla, E. “Robust Circular Logistic Regression Model and Its Application to Life and Social Sciences”. Revista Colombiana de Estadística, vol. 46, no. 1, Jan. 2023, pp. 45-62, doi:10.15446/rce.v46n1.101517.

Turabian

Castilla, Elena. “Robust Circular Logistic Regression Model and Its Application to Life and Social Sciences”. Revista Colombiana de Estadística 46, no. 1 (January 18, 2023): 45–62. Accessed March 28, 2025. https://revistas.unal.edu.co/index.php/estad/article/view/101517.

Vancouver

1.
Castilla E. Robust Circular Logistic Regression Model and Its Application to Life and Social Sciences. Rev. colomb. estad. [Internet]. 2023 Jan. 18 [cited 2025 Mar. 28];46(1):45-62. Available from: https://revistas.unal.edu.co/index.php/estad/article/view/101517

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CrossRef citations1

1. Elena Castilla, Abhik Ghosh. (2023). Robust Minimum Divergence Estimation for the Multinomial Circular Logistic Regression Model. Entropy, 25(10), p.1422. https://doi.org/10.3390/e25101422.

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