### 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.

**State Variable:**

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.

**System:**

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 vs.Mechanistic

*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.