Nonlinear regression metamodels: a systematic approach
by M. Isabel Reis dos Santos
International Journal of Simulation and Process Modelling (IJSPM), Vol. 5, No. 3, 2009

Abstract: This paper proposes an approach for systematic development of nonlinear regression metamodels for stochastic simulation. This approach provides the practitioner with a process for the construction of nonlinear metamodels in general, and includes statistical techniques for estimation and validation of nonlinear regression models. In order to ensure that the resulting metamodel is a valid substitute for the original simulation model, validation techniques are suggested. In a case study, the proposed application leads to simple function that adequately approximate the model's behaviour, while linear regression polynomials result in a poor fit.

Online publication date: Wed, 20-Jan-2010

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