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