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

This is a Preprint and has not been peer reviewed.

Downloads

Download Preprint

Supplementary Files
Authors

Jeremy Rohmer , manceau , Guyonnet , Boulahya , Dubois

Abstract

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.

DOI

https://doi.org/10.31223/osf.io/j67cy

Subjects

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

Keywords

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

Dates

Published: 2018-08-31 22:13

Older Versions
License

GNU Lesser General Public License (LGPL) 2.1

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.