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Research Article | Open Access

Generalized Chi distribution for non-integer degrees of freedom in modelling biological collectivities

Juan Carlos Castro-Palacio1Pedro Fernández de Córdoba2Álvaro González-Cortés2( )J. M. Isidro2A. Noverques3Marcos Orellana-Panchame1,4Sarira Sahu5Enrique A. Sánchez-Pérez2
Centro de Tecnologías Físicas, Universitat Politècnica de València, Camino de Vera, s/n, 46022 València, Spain
Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, Camino de Vera, s/n, 46022 Valencia, Spain
Institute for Industrial, Radiophysical and Environmental Safety (ISIRYM), Universitat Politècnica de València, Camino de Vera, s/n, 46022, València, Spain
Departamento de Matemática, Universidad Nacional Autónoma de Honduras (UNAH), 21102 San Pedro Sula, Honduras
Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Circuito Exterior, C.U., A. Postal 70-543, Mexico DF 04510, Mexico
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Abstract

This article aims to expand the practical potential of the Chi and Chi-square distributions by extending their applicability to non-integer degrees of freedom, k. The study has two main objectives: first, to explore and leverage the relationship between the Chi, Chi-square, and Gamma distributions to interpret non-integer degrees of freedom; and second, to apply this framework to real survival-time data in the context of biological and health sciences. Three specific cases are analyzed: the germination times of Pinus tropicalis Morelet seeds cultivated in western Cuba; the interval between infection by virulent tuberculous bacilli and death from tuberculosis in guinea pigs; and the period from the onset of symptoms to death due to COVID-19 in patients in Mexico during 2020. A parameter estimation was performed by maximum likelihood (MLE), and the optimal value of k was found to be non-integer in all cases.

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AIMS Mathematics
Pages 25033-25048

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Cite this article:
Castro-Palacio JC, de Córdoba PF, González-Cortés Á, et al. Generalized Chi distribution for non-integer degrees of freedom in modelling biological collectivities. AIMS Mathematics, 2025, 10(10): 25033-25048. https://doi.org/10.3934/math.20251109

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Received: 12 June 2025
Revised: 18 September 2025
Accepted: 30 September 2025
Published: 31 October 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)