scholarly journals A new method for finding the optimal smoothing parameter for the abstract smoothing spline

2010 ◽  
Vol 162 (6) ◽  
pp. 1117-1127 ◽  
Author(s):  
Alexander I. Rozhenko
Keyword(s):  
Smoothing Parameter ◽  
New Method ◽  
Smoothing Spline ◽  
Optimal Smoothing

Optimal Smoothing Spline with Constraints on Its Derivatives

2014 ◽  
Vol 7 (2) ◽  
pp. 104-111 ◽  
Author(s):  
Hiroyuki KANO ◽  
Hiroyuki FUJIOKA ◽  
Clyde F. MARTIN
Keyword(s):  
Smoothing Spline ◽  
Optimal Smoothing

Algorithms for Optimal Smoothing Parameter

2001 ◽  
pp. 243-262
Author(s):  
Anatoly Yu. Bezhaev ◽  
Vladimir A. Vasilenko
Keyword(s):  
Smoothing Parameter ◽  
Optimal Smoothing

On the equivalence of two stochastic approaches to spline smoothing

1986 ◽  
Vol 23 (A) ◽  
pp. 391-405 ◽  
Author(s):  
Craig F. Ansley ◽  
Robert Kohn
Keyword(s):  
Stochastic Process ◽  
Hilbert Space ◽  
Minimization Problem ◽  
Stochastic Models ◽  
Conditional Expectation ◽  
Smoothing Spline ◽  
Computational Algorithms ◽  
Spline Smoothing ◽  
Optimal Smoothing ◽  
Space Formulation

Wahba (1978) and Weinert et al. (1980), using different models, show that an optimal smoothing spline can be thought of as the conditional expectation of a stochastic process observed with noise. This observation leads to efficient computational algorithms. By going back to the Hilbert space formulation of the spline minimization problem, we provide a framework for linking the two different stochastic models. The last part of the paper reviews some new efficient algorithms for spline smoothing.

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