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research [2021/01/05 10:31] – [Practical uncertainty representations] sdestercresearch [2021/01/05 10:31] – [Uncertainty propagation and (in)dependence modelling] sdesterc
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 Work (mainly) benefiting from collaborations and discussions with D. Dubois, M. Troffaes, E. Miranda, L. Utkin, E. Chojnacki, E. Quaeghebeur and I. Montes Work (mainly) benefiting from collaborations and discussions with D. Dubois, M. Troffaes, E. Miranda, L. Utkin, E. Chojnacki, E. Quaeghebeur and I. Montes
  
-There exists many practical representations in imprecise probability theories, including possibility distributions, belief functions, imprecise probability assignments, pari-mutuel models, imprecise cumulative distributions (p-boxes), clouds, ...+There exist many practical representations in imprecise probability theories, including possibility distributions, belief functions, imprecise probability assignments, pari-mutuel models, imprecise cumulative distributions (p-boxes), clouds, ...
  
 Aside establishing new relations between the properties of several models (i.e. clouds, p-boxes, possibility distributions), we have proposed a model called generalized p-box that models uncertainty by probabilistic bounds over collection of nested sets. Such models appear naturally in elicitation procedures or statistical confidence structures, and first results indicates that generalized p-boxes may be an interesting non-parametric model to handle multivariate problems and/or to handle bipolar information.  Aside establishing new relations between the properties of several models (i.e. clouds, p-boxes, possibility distributions), we have proposed a model called generalized p-box that models uncertainty by probabilistic bounds over collection of nested sets. Such models appear naturally in elicitation procedures or statistical confidence structures, and first results indicates that generalized p-boxes may be an interesting non-parametric model to handle multivariate problems and/or to handle bipolar information. 
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 ====== Uncertainty propagation and (in)dependence modelling ====== ====== Uncertainty propagation and (in)dependence modelling ======
  
-Work (mainly) benefiting from collaborations and discussions with D. Dubois, G. De Cooman, E. Chojnacki, J. Baccou, T. Burger, M. Sallak, M.C.M. Troffaes, F. Coolen, S. Ferson, F. Aguirre and I. Sanchez+Work (mainly) benefiting from collaborations and discussions with D. Dubois, G. De Cooman, E. Chojnacki, J. Baccou, T. Burger, M. Sallak, M.C.M. Troffaes, F. Coolen, S. Ferson, F. Aguirre and I. Montes
  
 How to propagate uncertainty analysis in various models is an important issue that may face several difficulties. Most of my research in this domain has concerned the propagation of uncertainty model through deterministic functions with methods combining Monte-Carlo simulation and interval analysis, with an industrial risk-assessment purpose.  How to propagate uncertainty analysis in various models is an important issue that may face several difficulties. Most of my research in this domain has concerned the propagation of uncertainty model through deterministic functions with methods combining Monte-Carlo simulation and interval analysis, with an industrial risk-assessment purpose. 

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research.txt · Last modified: 2021/01/05 10:31 by sdesterc
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