Authors: | Davies, P. L. Meise, M. |
Title: | Approximating data with weighted smoothing splines |
Language (ISO): | de |
Abstract: | Given a data set (t_i, y_i), i = 1,... ,n with the t_i ∈ [0, 1] non-parametric regression is concerned with the problem of specifying a suitable function f_n : [0, 1] → R such that the data can be reasonably approximated by the points (t_i, f_n(t_i)), i = 1,... ,n. A common desideratum is that the function fn be smooth but the path towards this goal is often the indirect one of assuming a “true” data generating function f and then measuring performance by the expected mean square. The approach taken in this paper is a different one. We specify precisely what we mean by a function fn being an adequate approximation to the data and then, using weighted splines, we try to maximize the smoothness given the approximation constraints. |
Subject Headings: | Approximation Non-parametric regression Residuals Smoothing Splines Thin Plate Splines |
URI: | http://hdl.handle.net/2003/21759 http://dx.doi.org/10.17877/DE290R-15378 |
Issue Date: | 2005-12-14T09:10:34Z |
Appears in Collections: | Sonderforschungsbereich (SFB) 475 |
Files in This Item:
File | Description | Size | Format | |
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tr48-05.pdf | DNB | 2.67 MB | Adobe PDF | View/Open |
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