Spatially Adaptive Regression Splines and Accurate Knot Selection Schemes

By S. Zhou, Xiaotong Shen. 2001

144 citations recorded by the source corpus.

Subfields: Computational Mechanics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/4ae4896bd550091e0e98d125fc4959a18f9f7426

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Satoshi Miyata
2. Xiao Wang
3. Feng Li
4. Simon N. Wood
5. Xiaotong Shen
6. Jay Barlow
7. G. Simpson
8. Li Wang

In Signal Processing

1. Xiao Wang
2. Feng Li
3. Satoshi Miyata
4. Simon N. Wood
5. Xiaotong Shen

Citations in the corpus

• Thin plate regression splines (2003, background): “Another more subtle problem with the latter strategy is “knot confounding” (Zhou and Shen, 2001).”
• Isotonic Smoothing Spline Regression (2008, methodology): “Free knot splines (Zhou and Shen 2001) have been suggested in the literature as an adaptive method for curve fitting.”
• Adaptive Free-Knot Splines (2003, methodology): “The need for a more intelligentsearch scheme has driven recent work of Zhou and Shen (2001) on knot selection which uses knot relocation, guided search, and local tting.”
• Free‐knot polynomial splines with confidence intervals (2003, background): “Some more recent, effective variations are in Smith and Kohn (1996), Denison et al. (1998), Lindstrom (1999), DiMatteo et al. (2001) and Zhou and Shen (2001).”