In this paper we consider the semiparametric regression model, Y=x'[beta]+m(t)+[var epsilon], and provide some influence diagnostics for estimators of [beta], m and the mean response x'[beta]+m(t). We express these influence diagnostics as functions of the residuals and leverages. We find that...

In fitting parametric or nonparametric regression models, one or a few observations may have undue effects on estimators. These influential observations are precisely detected by the well-known influence measure, Cook's distance. In this paper, we introduce a type of Cook's distance for one or a...

We present a version of Cook's distance that is applicable to groups of observations in spline smoothing and can be used for outlier detection when masking is present. We express them as functions of the basic diagnostic building blocks: residuals and leverage values. An example based on a real...