Dynamical system and nonlinear regression for estimate host-parasitoid relationship
type: Item
instance of: scholarly article
title: Dynamical system and nonlinear regression for estimate host-parasitoid relationship
zbMATH Open document ID: 1211.37103
DOI: 10.1155/2010/851037
author: Ileana Miranda Cabrera
author: Heyker Lellanis Baños Díaz
author: María De Los Ángeles Martínez
published in: Journal of Applied Mathematics
publication date: 2010-12-17T00:00:00Z
review text: The authors presents a dynamical system for studying the relationship host-parasitoid which permits the estimation of the parasite nymphs using nymphs healthy as the known variable. The model shows the functional answer of the parasitoid, in which a point arrives that its density is not augmented although the number host increases, and it becomes necessary to intervene in the ecosystem. By using a simple algorithm, the authors estimate the parasitoids level using the priori relationship between the host and the climate factors and then the nonlinear model. They study the relation host-parasitoid and use the random sequential samples to do regression models to estimate the parasitoid percent knowing the density host in the crop.
Mathematics Subject Classification ID: 37N25
Mathematics Subject Classification ID: 91D25
Mathematics Subject Classification ID: 92D40
zbMATH DE Number: 5827513
zbMATH Keywords: host-parasitoid relationship
zbMATH Keywords: nonlinear regression
zbMATH Keywords: stability
reviewed by: Xueyong Zhou
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2010/851037
OpenAlex ID: W1971865379
Wikidata QID: Q58652435
cites work: Mathematical study of the growth of tetranichidae mites under-field conditions: relationship prey-predator
cites work: Q4382864
cites work: Dynamical systems analysis of a five-dimensional trophic food web model in the southern oceans
DBLP publication ID: journals/jam/CabreraDM10
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description: scientific article; zbMATH DE number 5827513