 The use of augmented loss functions for estimating dynamic energy budget parametersKonstadia Lika, Starrlight Augustine and Sebastiaan A.L.M. Kooijman Ecological Modelling, 2020, vol. 428, issue C Abstract: We propose an extension of a parameter-free loss function for the estimation of Dynamic Energy Budget parameters for a set of related species that is symmetric in the role of data and predictions. The extension allows that particular parameters might vary, but not by much, among species, while the degree of variation is controlled by weight coefficients. We discuss the choice of these coefficients and illustrate the application with an example of two species of catfish, with their mutual hybrids. In our simultaneous parameter estimation for this example, we could reduce the variation in a parameter, here the energy conductance, substantially with a minor effect on the goodness of fit. We selected this parameter among the ones that varied, because its value was poorly determined by the data. We discuss this example in some detail. The software for implementing this augmented loss function has been implemented in the available software DEBtool_M on Github (www.github.com/add-my-pet/DEBtool_M). Keywords: Dynamic energy budget theory; Symmetric loss functions; Regularization of parameter estimation; Parameter estimation in context; Add-my-Pet; Clarias & Heterobranchus (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:428:y:2020:i:c:s0304380020301824 DOI: 10.1016/j.ecolmodel.2020.109110 Access Statistics for this article Ecological Modelling is currently edited by Brian D. Fath More articles in Ecological Modelling from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.