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Smoothing Methods in Regression

Smoothing Methods in Regression

陈傲天
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How much smoothing should we do? Approximation by local averaging. How much smoothing we should do to find the unknown curve depends on how smooth the curve really is, which is unknown. Adaptation as a partial substitute for actual knowledge. Cross-validation for adapting to unknown smoothness. Application: testing parametric regression models by comparing them to nonparametric fits. The bootstrap principle. Why ever bother with parametric regressions?
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