An Adaptive Knot Selection Method for Regression Splines via Penalized Minimum Contrast Estimation
- 2015-06-15 (Mon.), 10:30 AM
- 中研院-統計所 2F 交誼廳
- 茶 會:上午10:10統計所二樓交誼廳
- 黃 子 銘 教授
- 國立政治大學統計學系
Abstract
In this talk, a knot selection method for regression splines will be presented. This method yields a penalized least square spline estimator that is adaptive and allows for non-equally spaced knots. If the regression function belongs to a Sobolev space, then the penalized least square spline estimator can converge to the regression function at a nearly optimal rate.
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