Uncertainty quantification and management.

The package uncertainty provides several functionalities to quantify and manage uncertainties. Most of them can be used from the dedicated API.

The sub-package distributions offers an abstract level for probability distributions as well as interfaces to the OpenTURNS and SciPy ones. It is also possible to fit a probability distribution from data or select the most likely one from a list of candidates. These distributions can be used to define random variables in a ParameterSpace before propagating these uncertainties through a system of MDODiscipline, by means of a DOEScenario.

The sub-package sensitivity offers an abstract level for sensitivity analysis, as well as concrete features. These sensitivity analyses compute indices by means of various methods: correlation measures, Morris technique and Sobol’ variance decomposition. This sub-package is based in particular on OpenTURNS.

The sub-package statistics offers an abstract level for statistics, as well as parametric and empirical versions. Empirical statistics are estimated from a Dataset while parametric statistics are analytical properties of a Distribution fitted from a Dataset.