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A stochastic framework for recursive computation of spline functions: Part II,smoothing splines |
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| Authors: | H L Weinert R H Byrd G S Sidhu |
| Institution: | (1) Department of Electrical Engineering, The Johns Hopkins University, Baltimore, Maryland;(2) Department of Mathematical Sciences, The Johns Hopkins University, Baltimore, Maryland;(3) Instituto de Investigaciones en Matematicas Aplicadas y en Sistemas, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico |
| Abstract: | Many of the optimal curve-fitting problems arising in approximation theory have the same structure as certain estimation problems involving random processes. We develop this structural correspondence for the problem of smoothing inaccurate data with splines and show that the smoothing spline is a sample function of a certain linear least-squares estimate. Estimation techniques are then used to derive a recursive algorithm for spline smoothing. |
| Keywords: | Splien smoothing reproducing kernels least-squares estimation recursive algorithms |
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