Glossary

parameter uncertainty
An uncertainty is a parameter uncertainty if the range is continuous from the lower bound to the upper bound. A parameter uncertainty can be either real valued or discrete valued.
categorical uncertainty
An uncertainty is categorical if there is not a range but a set of possibilities over which one wants to sample.
lookup uncertainty
vensim specific extension to categorical uncertainty for handling lookups in various ways
uncertainty space
the space created by the set of uncertainties
ensemble
a python class responsible for running a series of computational experiments.
model interface
a python class that provides an interface to an underlying model
working directory
a directory that contains files that a model needs
classification trees
a category of machine learning algorithms for rule induction
prim (patient rule induction method)
a rule induction algorithm
coverage
a metric developed for scenario discovery
density
a metric developed for scenario discovery
scenario discovery
a use case of EMA
case
A case specifies the input parameters for a run of a model. It is a dict instance, with the names of the uncertainties as key, and their sampled values as value.
experiment
An experiment is a complete specification for a run. It specifies the case, the name of the policy, and the name of the model.
policy
a policy is by definition an object with a name attribute. So, policy[‘name’] most return the name of the policy
result
the combination of an experiment and the associated outcomes for the experiment
outcome
the data of interest produced by a model given an experiment