Abstract
In the first part of this paper we apply a saddle point theorem from convex analysis to show that various constrained minimization problems are equivalent to the problem of smoothing by spline functions. In particular, we show that near-interpolants are smoothing splines with weights that arise as Lagrange multipliers corresponding to the constraints in the problem of near-interpolation. In the second part of this paper we apply certain fixed point iterations to compute these weights. A similar iteration is applied to the computation of the smoothing parameter in the problem of smoothing.
| Original language | English |
|---|---|
| Pages (from-to) | 1873-1885 |
| Number of pages | 13 |
| Journal | Mathematics of Computation |
| Volume | 72 |
| Issue number | 244 |
| State | Published - Oct 2003 |
Scopus Subject Areas
- Algebra and Number Theory
- Computational Mathematics
- Applied Mathematics
Keywords
- Approximation
- Near-interpolation
- Smoothing splines
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