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Prestes Garcia, Antonio (2016). Sensitivity analysis of Repast computational ecology models with R/Repast. "Ecology And Evolution", v. 6 (n. 24); pp. 8811-8831. ISSN 2045-7758. https://doi.org/10.1002/ece3.2580.
Title: | Sensitivity analysis of Repast computational ecology models with R/Repast |
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Author/s: |
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Item Type: | Article |
Título de Revista/Publicación: | Ecology And Evolution |
Date: | December 2016 |
ISSN: | 2045-7758 |
Volume: | 6 |
Subjects: | |
Faculty: | E.T.S. de Ingenieros Informáticos (UPM) |
Department: | Inteligencia Artificial |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual-based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities or populations due to individual variability. In addition, being a bottom up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in silico experimental setup. In this paper we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results.
Item ID: | 46237 |
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DC Identifier: | https://oa.upm.es/46237/ |
OAI Identifier: | oai:oa.upm.es:46237 |
DOI: | 10.1002/ece3.2580 |
Official URL: | https://onlinelibrary.wiley.com/doi/full/10.1002/e... |
Deposited by: | Memoria Investigacion |
Deposited on: | 22 Jun 2017 09:38 |
Last Modified: | 04 Jun 2019 08:49 |