Review of Model Type (EPA, 2009a; 2009c)
Probabilistic vs. Deterministic
Probabilistic models are sometimes referred to as statistical or stochastic models. These models utilize the entire range of input data to develop a probability distribution of model output for the state variable(s).
Deterministic models provide a solution for the state variable(s) rather than a set of probabilistic outcomes.
The dependent variables calculated within the model which are also often the performance indicators of the models that change over the simulation.
Dynamic vs. Static
Dynamic models makes predictions about the way a system changes with time or space.
A collection of objects or variables and the relations among them.
Static models make predictions about the way a system changes as the value of an independent variable changes.
Empirical models include very little information on the underlying mechanisms and rely upon the observed relationship among experimental data.
Mechanistic models explicitly include the mechanisms or processes between the state variables. The parameters in mechanistic models should be supported by data and have real-world interpretations.