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dc.contributor.authorJanssen PHM
dc.contributor.authorSlob W
dc.contributor.authorRotmans J
dc.date.accessioned2012-12-12T16:29:10Z
dc.date.available2012-12-12T16:29:10Z
dc.date.issued1990-07-31
dc.identifier958805001
dc.identifier.urihttp://hdl.handle.net/10029/258049
dc.description.abstractMathematical models are useful tools for studying many problems in the environmental and public health area. For a reliable development and application of these models modelanalysis has to be an indispensable part of the total modelling process. This modelanalysis usually consists of performing sensitivity- and uncertainty analyses to the model. In this report a methodology is presented for these analyses and a survey is given of available techniques. Moreover some currently used measures for quantifying the uncertainty contribution of the various sources of uncertainty are critically evaluated and improved.<br>
dc.description.sponsorshipRIVM
dc.formatapplication/pdf
dc.format.extent126 p
dc.format.extent5909 kb
dc.language.isonl
dc.publisherRijksinstituut voor Volksgezondheid en Milieu RIVM
dc.relation.ispartofRIVM Rapport 958805001
dc.relation.urlhttp://www.rivm.nl/bibliotheek/rapporten/958805001.html
dc.relation.urlhttp://www.rivm.nl/bibliotheek/rapporten/958805001.pdf
dc.subject20nl
dc.subjectwiskundige modellennl
dc.subjectmodelanalysenl
dc.subjectonzekerheidsanalyse; gevoeligheidsanalysenl
dc.subjectrisico-analysenl
dc.subjectregressienl
dc.subjectcorrelatie; methodologienl
dc.titleGevoeligheidsanalyse en onzekerheidsanalyse: een inventarisatie van ideeen, methoden en techniekennl
dc.title.alternativeSensitivity analysis and uncertainty analysis: an inventory of ideas, methods and techniquesen
dc.typeReport
dc.date.updated2012-12-12T16:29:11Z
html.description.abstractMathematical models are useful tools for studying many problems in the environmental and public health area. For a reliable development and application of these models modelanalysis has to be an indispensable part of the total modelling process. This modelanalysis usually consists of performing sensitivity- and uncertainty analyses to the model. In this report a methodology is presented for these analyses and a survey is given of available techniques. Moreover some currently used measures for quantifying the uncertainty contribution of the various sources of uncertainty are critically evaluated and improved.&lt;br&gt;


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