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.
| Version: | 1.2 |
| Depends: | R (≥ 3.5), AlgDesign, copula, evd, triangle, kolmim |
| Published: | 2019-01-07 |
| Author: | Philipp Limbourg |
| Maintainer: | Philipp Limbourg <p.limbourg at uni-due.de> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Citation: | ipptoolbox citation info |
| CRAN checks: | ipptoolbox results |
| Reference manual: | ipptoolbox.pdf |
| Package source: | ipptoolbox_1.2.tar.gz |
| Windows binaries: | r-devel: ipptoolbox_1.2.zip, r-release: ipptoolbox_1.2.zip, r-oldrel: ipptoolbox_1.2.zip |
| macOS binaries: | r-release: ipptoolbox_1.2.tgz, r-oldrel: ipptoolbox_1.2.tgz |
| Old sources: | ipptoolbox archive |
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