Uninet
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 net.
Download the latest installer (registration required) : Download page (Installer size 11.6MB)
Read Uninet help file describing the software in detail: UninetHelp.pdf (opens in new window, size 2.2 MB)
Screenshots
1. Random variables view - specify input random variables for your model and assign distributions.
![](https://filelist.tudelft.nl/EWI/Over%20de%20faculteit/Afdelingen/Applied%20Mathematics/Applied%20Probability/Risk/Software/uninet/1.png)
2. Bayesian Belief Net view - build your model with probabilistic nodes, functional nodes and arcs.
![](https://filelist.tudelft.nl/EWI/Over%20de%20faculteit/Afdelingen/Applied%20Mathematics/Applied%20Probability/Risk/Software/uninet/2.png)
3. Specify (conditional) rank correlation coefficients on the arcs.
![](https://filelist.tudelft.nl/EWI/Over%20de%20faculteit/Afdelingen/Applied%20Mathematics/Applied%20Probability/Risk/Software/uninet/3.png)
4. Specify formulae for functional nodes.
![](https://filelist.tudelft.nl/EWI/Over%20de%20faculteit/Afdelingen/Applied%20Mathematics/Applied%20Probability/Risk/Software/uninet/4.png)
5. Sample the model and view results.
![](https://filelist.tudelft.nl/EWI/Over%20de%20faculteit/Afdelingen/Applied%20Mathematics/Applied%20Probability/Risk/Software/uninet/5.png)
6. Call satellite programs for further analysis of the sample.
![](https://filelist.tudelft.nl/EWI/Over%20de%20faculteit/Afdelingen/Applied%20Mathematics/Applied%20Probability/Risk/Software/uninet/8.png)
7. Explore multivariate joint distributions with Unigraph .
![](https://filelist.tudelft.nl/EWI/Over%20de%20faculteit/Afdelingen/Applied%20Mathematics/Applied%20Probability/Risk/Software/uninet/6.png)
8. Carry out sensitivity analysis with Unisens .
![](https://filelist.tudelft.nl/EWI/Over%20de%20faculteit/Afdelingen/Applied%20Mathematics/Applied%20Probability/Risk/Software/uninet/7.png)
8. Carry out sensitivity analysis with Unisens .