Title: Nonlinear regression metamodels: a systematic approach

Authors: M. Isabel Reis dos Santos

Addresses: Department of Mathematics, Center for Management Studies (CEGIST), Technical University of Lisbon (TULisbon), Av. Rovisco Pais, 1, Lisbon 1049-001, Portugal

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.

Keywords: metamodelling; discrete event simulation; nonlinear regression metamodels; metamodel estimation; metamodel validation; methodology.

DOI: 10.1504/IJSPM.2009.031098

International Journal of Simulation and Process Modelling, 2009 Vol.5 No.3, pp.241 - 255

Received: 01 May 2009
Accepted: 11 Jun 2009
Published online: 20 Jan 2010 *

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