HYRISK: An R package for hybrid uncertainty analysis using probability, imprecise probability and possibility distributions

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Jeremy Rohmer, Jean-Charles Manceau, Dominique Guyonnet, Faiza Boulahya, Didier Dubois


Uncertainty analysis is an unavoidable risk assessment task (for instance for natural hazards, or for environmental issues). In situations where data are scarce, incomplete or imprecise, the systematic and only use of probabilities can be debatable. Over the last years, several alternative mathematical representation methods have been developed to handle in a more flexible manner the lack of knowledge related to input parameters of risk assessment models. This article presents an R package HYRISK dedicated to jointly handling different mathematical representation tools, namely probabilities, possibility distributions and probability functions with imprecise parameters, for the different stages of uncertainty treatment in risk assessments (i.e. uncertainty representation, propagation, sensitivity analysis and decision-making). We support the description using the case study of a dike stability analysis. The package is available at: https://cran.r-project.org/web/packages/HYRISK/index.html.




Applied Mathematics, Engineering, Ordinary Differential Equations and Applied Dynamics, Other Applied Mathematics, Physical Sciences and Mathematics, Risk Analysis


uncertainty, Sensitivity analysis, R Programming, p-box, possibility, probability, quantification


Published: 2018-08-31 10:13

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GNU Lesser General Public License (LGPL) 2.1

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