RESIDUAL VARIANCE AND RESIDUAL PATTERN IN NONLINEAR-REGRESSION
成果类型：
Article
署名作者：
GASSER, T; SROKA, L; JENNENSTEINMETZ, C
署名单位：
Ruprecht Karls University Heidelberg
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
发表日期：
1986
页码：
625633
关键词：
摘要：
A nonparametric estimator of residual variance in nonlinear regression is proposed. It is based on local linear fitting. Asymptotically the estimator has a small bias, but a larger variance compared with the parametric estimator in linear regression. Finite sample properties are investigated in a simulation study, including a comparison with other nonparametric estimators. The method is also useful for spotting heteroscedasticity and outliers in the residual at an early stage of the data analysis. A further application is checking the fit of parametric models. This is illustrated for longitudinal growth data.