Difference between revisions of "Grey box model"
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Latest revision as of 07:38, 26 May 2016
In mathematics, statistics, and computational modelling, a grey box model combines a partial theoretical structure with data to complete the model.
Description
The theoretical structure may vary from information on the smoothness of results, to models that need only parameter values from data or existing literature.
Thus, almost all models are grey box models as opposed to black box where no model form is assumed, or white box models that are purely theoretical.
Some models assume a special form such as a linear regression or neural network.
These have special analysis methods. In particular, linear regression techniques are much more efficient than most non-linear techniques.
The model can be deterministic or stochastic (i.e. containing random components) depending on its planned use.
See also
- Computational modelling
- Computer experiment
- Computer simulation
- Design of experiments
- Grey box testing
- Linear regression
- Mathematical model
- Nonlinear system identification
- Parameter estimation
- Research design
- Scientific modelling
- Simulation
- Statistics
- Statistical model
- Stochastic process
- System dynamics
- System identification
- System realization
- Systems theory
External links
- Grey box model @ Wikipedia
