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July, 1974 Stochastic Interpretations and Recursive Algorithms for Spline Functions
Howard L. Weinert, Thomas Kailath
Ann. Statist. 2(4): 787-794 (July, 1974). DOI: 10.1214/aos/1176342765


Spline functions, which are solutions to certain deterministic optimization problems, can also be regarded as solutions to certain stochastic optimization problems; in particular, certain linear least-squares estimation problems. Such an interpretation leads to simple recursive algorithms for interpolating and smoothing splines. These algorithms compute the spline using one data point at a time, and are useful in real-time calculations when data are acquired sequentially.


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Howard L. Weinert. Thomas Kailath. "Stochastic Interpretations and Recursive Algorithms for Spline Functions." Ann. Statist. 2 (4) 787 - 794, July, 1974.


Published: July, 1974
First available in Project Euclid: 12 April 2007

zbMATH: 0287.65009
MathSciNet: MR384290
Digital Object Identifier: 10.1214/aos/1176342765

Keywords: $Lg$-splines , 62 85 , 65 20 , least-squares estimation , recursive spline interpolation , recursive spline smoothing , ‎reproducing kernel Hilbert ‎space , Spline functions , stochastic interpretation

Rights: Copyright © 1974 Institute of Mathematical Statistics


Vol.2 • No. 4 • July, 1974
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