TITLE:
Local Curvature and Centering Effects in Nonlinear Regression Models
AUTHORS:
Michael Brimacombe
KEYWORDS:
Nonlinear Regression, Centering Data, Model Mis-Specification, Bias, Curvature
JOURNAL NAME:
Open Journal of Statistics,
Vol.6 No.1,
February
23,
2016
ABSTRACT: The effects of centering response and
explanatory variables as a way of simplifying fitted linear models in the
presence of correlation are reviewed and extended to include nonlinear models,
common in many biological and economic applications. In a nonlinear model, the
use of a local approximation can modify the effect of centering. Even in the
presence of uncorrelated explanatory variables, centering may affect linear
approximations and related test statistics. An approach to assessing this
effect in relation to intrinsic curvature is developed and applied.
Mis-specification bias of linear versus nonlinear models also reflects this
centering effect.