Nonlinear regression metamodels: a systematic approach. (22nd January 2010) - Reis dos Santos, M. Isabel
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.