Backfitting Estimation of a Response Surface Model

Year: 2010       Vol.: 59       No.: 1      

Authors: Jhoanne Marsh C. Gatpatan

Abstract:

The backfitting algorithm is used in estimating a response surface model with covariates from a data generated through a central composite design. Backfitting takes advantage of the orthogonality generated by the central composite design on the design matrix. The simulation study shows that backfitting yield estimates and predictive ability of the model comparable to that from ordinary least squares when the response surface bias is minimal. Ordinary least squares estimates generally fails when the response surface bias is large, while backfitting exhibits robustness and still produces reasonable estimates and predictive ability of the fitted model. Orthogonality facilitates the viability of assumptions in an additive model where backfitting is an optimal estimation algorithm.

Keywords: backfitting; response surface model; second order model; central composite design

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