An evaluation of global sensitivity analysis methods applied to an ecological competition model

dc.contributor.author Hou, Jing
dc.contributor.department Statistics
dc.contributor.majorProfessor Philip Dixon
dc.date 2021-09-01T04:44:56.000
dc.date.accessioned 2021-09-09T16:53:41Z
dc.date.available 2021-09-09T16:53:41Z
dc.date.copyright Fri Jan 01 00:00:00 UTC 2021
dc.date.embargo 2021-07-02
dc.date.issued 2021-01-01
dc.description.abstract <p>Sensitivity analysis (SA) is a useful tool to identify important parameters that affect model performance and it plays an important role in model parameterization, calibration, optimization, and uncertainty quantification. In this study, two popular global SA methods, the Morris and Sobol methods, are applied to an ecological competition model, which simulates the temporal dynamics of coral reef communities with 29 parameters. Both of the results obtained by the Morris and Sobol methods show that there are higher interactions in states 3 and 5 compared with other states. Moreover, the two methods provide very similar results for influential and non-influential model parameters. To achieve sufficient precision, the Sobol method requires 1000 repetitions, while the Morris method only requires 100 repetitions. Overall, the results of this study reveal that the Morris method is capable of producing a highly similar set of the most influential and non-influential parameters as that obtained by Sobol’s method but with less computation cost. For complex models with a large number of parameters or expensive computations, the method of Morris may be an efficient way to identify parameter sensitivities.</p>
dc.format.mimetype PDF
dc.identifier archive/lib.dr.iastate.edu/creativecomponents/856/
dc.identifier.articleid 1920
dc.identifier.contextkey 23640867
dc.identifier.doi https://doi.org/10.31274/cc-20240624-171
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath creativecomponents/856
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/dvmqJWXv
dc.source.bitstream archive/lib.dr.iastate.edu/creativecomponents/856/thesis_Jing_Hou.pdf|||Sat Jan 15 02:13:21 UTC 2022
dc.subject.disciplines Applied Statistics
dc.subject.keywords Sensitivity analysis
dc.subject.keywords Morris method
dc.subject.keywords Sobol method
dc.subject.keywords Competition model
dc.title An evaluation of global sensitivity analysis methods applied to an ecological competition model
dc.type article
dc.type.genre creativecomponent
dspace.entity.type Publication
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
thesis.degree.discipline Statistics
thesis.degree.level creativecomponent
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