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Sensitivity analysis of Repast Computational Ecology models with R/Repast

Antonio Prestes García; Alfonso Rodríguez-Patón

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  <identifier identifierType="DOI">10.5281/zenodo.160954</identifier>
      <creatorName>Antonio Prestes García</creatorName>
      <affiliation>Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid</affiliation>
      <creatorName>Alfonso Rodríguez-Patón</creatorName>
      <affiliation>Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid</affiliation>
    <title>Sensitivity analysis of Repast Computational Ecology models with R/Repast</title>
    <subject>Individual-Based Modeling, Sensitivity analysis, Repast, Computational Ecology, Systems Biology</subject>
    <date dateType="Issued">2016-10-15</date>
  <resourceType resourceTypeGeneral="JournalArticle"/>
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    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;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.&lt;br&gt;
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/FP7/612146/">612146</awardNumber>
      <awardTitle>Engineering multicellular biocircuits: programming cell-cell communication using plasmids as wires</awardTitle>
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