Modeling Risk of Extreme Events in Generalized Verhulst Models

Autor:	M. Fátima Brilhante, M. Ivette Gomes, Dinis Pestana
Jazyk:	angličtina
Rok vydání:	2019
Předmět:	Extreme value distributions generalized Verhulst models growth and retroaction parameters max-geometric-stable distributions population dynamics Statistics HA1-4737 Probabilities. Mathematical statistics QA273-280
Zdroj:	Revstat Statistical Journal, Vol 17, Iss 2 (2019)
Druh dokumentu:	article
ISSN:	1645-6726 2183-0371
DOI:	10.57805/revstat.v17i2.262
Popis:	A very popular model in population dynamics, which has been around since the first half of the nineteenth century, is the Verhulst logistic model. However, some limitations of this model have provided grounds to propose more sophisticated growth models using, for instance, the former as a basis. Since the Verhulst model and some generalizations of it are closely connected to extreme value distributions, either max-geometric-stable or max-stable, we show that the parameter attached to the retroaction factor of these generalized models establishes, on its own, which extreme value distribution is adequate to model risks of extreme events in population dynamics.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/0585f612f7114553b2b94f35a75e026d Zobrazit plný text záznamu View record in DOAJ