Uninet is a standalone uncertainty analysis software package. Its main focus is dependence modelling for high dimensional distributions. Random variables can be coupled using a Bayesian belief network, dependence trees or probability vines.
Download the latest installer: Download Page
Read Uninet help file describing the software in detail: UninetHelp.pdf (document size 2.1 MB)
1. Random variables view – specify input random variables for your model and assign distributions.
2. Bayesian Belief Net view – build your model with probabilistic nodes, functional nodes and arcs.
3. Specify (conditional) rank correlation coefficients on the arcs.
4. Specify formulae for functional nodes.
5. Sample the model and view results.
6. Call satellite programs for further analysis of the sample.
7. Explore multivariate joint distributions with Unigraph.
8. Carry out sensitivity analysis with Unisens.
And many more features to discover!