A methodology for fitting and validating metamodels in simulation
This expository paper discusses the relationships among metamodels, simulation models, and problem entities.A metamodel or response surface is an approximation of the input/output function implied by the underlying simulation model.Common criticisms that we have encountered are described, and for each one we attempt to give a balanced perspective of the criticism.A model of intra-state conflict is ..." Using multi-agent models to study social systems has attracted criticisms because of the challenges involved in their validation.There are several types of metamodel: linear regression, splines, neural networks, etc.This paper distinguishes between fitting and validating a metamodel.
Metamodels in general are covered, along with a procedure for developing linear regression (including polynomial) metamodels.
Additionally, and not incidentally, an objective of any system simulation must be to achieve a certain measure of understanding of the nature of the relationships between the input variables and the output variables of the real system under study.
The simulation model, although simpler than the real-world system, is still a very complex way of relating input to output.
Metamodels may have different goals: (i) understanding, (ii) prediction, (iii) optimization, and (iv) verification and validation.
For this metamodeling, a process with thirteen steps is proposed.