Titlebook: Nonparametric Smoothing and Lack-of-Fit Tests; Jeffrey D. Hart Book 1997 Springer Science+Business Media New York 1997 Calc.Mathematica.Sc

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Statistical Properties of Smoothers,sion function, it becomes important to understand their statistical properties. In this chapter we discuss issues such as mean squared error and sampling distribution of an estimator, and using smoothers to obtain confidence intervals for values of the regression function. We will consider two types

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Data-Driven Lack-of-Fit Tests for General Parametric Models, case of a linear model, i.e., the case where . is hypothesized to be a linear combination of known functions. The fit of such models can be tested by applying the methods of Chapter 7 to residuals. It will be argued that test statistics generally have the same distributions they had in Chapter 7 .

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