Improved inference in nonparametric regression using Lk-Smoothing splines
نویسندگان
چکیده
Smoothing splines are one of the most popular approaches to nonparametric regression. Wahba (J. Roy. Statist. Soc. Set. B 40 (1978) 364-372; 45 (1983) 133-150) showed that smoothing splines are also Bayes estimates and used the corresponding prior model to derive interval estimates for the regression function. Although the interval estimates work well on a global basis, they can have poor local properties. The source of this problem is the use of a global smoothing parameter. We introduce the notion of L ksmoothing splines. These splines allow for a variable smoothing parameter and can substantially improve local inference. A M S Subject Classification: 62G05, 62G15
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IMPROVED INFERENCE IN NONPARAMETRICREGRESSION USING Lk -
Smoothing splines are one of the most popular approaches to nonparametric regression. Wahba (1978,1983) showed that smoothing splines are also Bayes estimates and used the corresponding prior model to derive interval estimates for the regression function. Although the interval estimates work well on a global basis, they can have poor local properties. The source of this problem is the use of a ...
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