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    A methodology for fitting and validating metamodels in simulation

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    Computer simulations have become a useful part of mathematical modeling of many natural systems in physics, astrophysics, chemistry and biology, human systems in economics, psychology, social science, and engineering.

    The norm is usually Euclidean distance, although other distance functions are also possible. Overfitting generally occurs when a model is excessively complex, such as having too many parameters relative to the number of observations.

    In statistics, response surface methodology (RSM) explores the relationships between several explanatory variables and one or more response variables. A model which has been overfit will generally have poor predictive performance, as it can exaggerate minor fluctuations in the data.

    A model is an abstraction of phenomena in the real world; a metamodel is yet another abstraction, highlighting properties of the model itself.

    A model conforms to its metamodel in the way that a computer program conforms to the grammar of the programming language in which it is written.

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