Uncertainty quantification and propagation in the framework of Dempster-Shafer Theory and imprecise probabilities. This toolbox offers easy-to-use methods for using imprecise probabities for applied uncertainty modelling and simulation. The package comprises the basic functionality needed, with usability similar to standard probabilistic analysis: - Fit imprecise probability distributions from data, - Define imprecise probabilities based on distribution functions, - Combine with various aggregation rules (e. g. Dempster's rule), - Plotting tools, - Propagate through arbitrary functions / simulations via Monte Carlo, - Perform sensitivity analyses with imprecise distributions, - Example models for a quick start.
|Author||Philipp Limbourg <firstname.lastname@example.org>|
|Maintainer||Philipp Limbourg <email@example.com>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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