Uncertainty quantification and propagation in the framework of DempsterShafer Theory and imprecise probabilities. This toolbox offers easytouse 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.
Package details 


Author  Philipp Limbourg <p.limbourg@unidue.de> 
Maintainer  Philipp Limbourg <p.limbourg@unidue.de> 
License  GPL (>= 2) 
Version  1.2 
Package repository  View on CRAN 
Installation 
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