Dealing with variability in ecological modelling: An analysis of a random non‐autonomous logistic population model

This paper presents a methodology to deal with the randomness associated to ecological modelling. Data variability makes it necessary to analyse the impact of random perturbations on the fitted model parameters. We conduct such analysis for the logistic growth model with a certain sigmoid functional...

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Published inMathematical methods in the applied sciences Vol. 45; no. 6; pp. 3318 - 3333
Main Authors Calatayud, Julia, Cortés, Juan Carlos, Dorini, Fábio A., Jornet, Marc
Format Journal Article
LanguageEnglish
Published Freiburg Wiley Subscription Services, Inc 01.04.2022
Subjects
Carrying capacity
Growth models
Impact analysis
logistic growth model
Mathematical models
Maximum entropy
Modelling
Parameters
Perturbation
probability density function
random parameters
Random variables
time‐varying carrying capacity
Variability
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ISSN0170-4214
1099-1476
DOI10.1002/mma.7458

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Summary:This paper presents a methodology to deal with the randomness associated to ecological modelling. Data variability makes it necessary to analyse the impact of random perturbations on the fitted model parameters. We conduct such analysis for the logistic growth model with a certain sigmoid functional form of the carrying capacity, which was proposed in the literature for the study of parasite growth during infection. We show how the probability distributions of the parameters are set via the maximum entropy principle. Then the random variable transformation method allows for computing the density function of the population.
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ISSN:0170-4214
1099-1476
DOI:10.1002/mma.7458