Weighted least squares estimators in possibly misspecified nonlinear regression

被引：0

作者：

Ursula U. Müller

机构：

[1] Texas A&M Univeristy,Department of Statistics

来源：

Metrika | 2007年 / 66卷

关键词：

Conditional mean model; Efficient estimation; Estimating equation; Influence function; Misspecification;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The behavior of estimators for misspecified parametric models has been well studied. We consider estimators for misspecified nonlinear regression models, with error and covariates possibly dependent. These models are described by specifying a parametric model for the conditional expectation of the response given the covariates. This is a parametric family of conditional constraints, which makes the model itself close to nonparametric. We study the behavior of weighted least squares estimators both when the regression function is correctly specified, and when it is misspecified and also involves possible additional covariates.

引用

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