Local Curvature and Centering Effects in Nonlinear Regression Models  

作　　者：Michael Brimacombe Michael Brimacombe(Department of Biostatistics, KUMC, Kansas City, KS, USA)

机构地区：[1]Department of Biostatistics, KUMC, Kansas City, KS, USA

出　　处：《Open Journal of Statistics》2016年第1期76-84,共9页统计学期刊（英文）

摘　　要：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.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.

关 键 词：Nonlinear Regression Centering Data Model Mis-Specification BIAS CURVATURE 

分 类 号：O17[理学—数学]