The probabilistic model makes it possible to define the probability distributions for each of your parameters. A large number of distributions are available, both continuous and discrete. You may also define the correlation between your variables thanks to copulas.
Defining the probabilistic model unlocks some features in Persalys such as:
- Sensitivity analysis
- Central tendency analysis
- Reliability analysis
For more information on how to create a probabilistic model, refer to the following video (soon in English):