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Modeling Dependence and Assessing the Effect of Uncertainty in Dependence in Probabilistic Analysis and Decision Under Uncertainty University of Toledo

SAE Technical Papers (1906-current) Available online

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Format:
Conference/Event
Author/Creator:
Nikolaidis, Nikolaidis, author.
Contributor:
Mourelatos, Zissimos P.
Conference Name:
SAE 2010 World Congress & Exhibition (2010-04-13 : Detroit, Michigan, United States)
Language:
English
Physical Description:
1 online resource
Place of Publication:
Warrendale, PA SAE International 2010
Summary:
A complete probabilistic model of uncertainty in probabilistic analysis and design problems is the joint probability distribution of the random variables. Often, it is impractical to estimate this joint probability distribution because the mechanism of the dependence of the variables is not completely understood. This paper proposes modeling dependence by using copulas and demonstrates their representational power. It also compares this representation with a Monte-Carlo simulation using dispersive sampling
Notes:
Vendor supplied data
Publisher Number:
2010-01-0697
Access Restriction:
Restricted for use by site license

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