Stochastic Interpretations and Recursive Algorithms for Spline Functions
Weinert, Howard L. ; Kailath, Thomas
Ann. Statist., Tome 2 (1974) no. 1, p. 787-794 / Harvested from Project Euclid
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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.
Publié le : 1974-07-14
Classification:  62 85,  65 20,  Spline functions,  $Lg$-splines,  recursive spline interpolation,  recursive spline smoothing,  stochastic interpretation,  least-squares estimation,  reproducing kernel Hilbert space 
@article{1176342765,
     author = {Weinert, Howard L. and Kailath, Thomas},
     title = {Stochastic Interpretations and Recursive Algorithms for Spline Functions},
     journal = {Ann. Statist.},
     volume = {2},
     number = {1},
     year = {1974},
     pages = { 787-794},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176342765}
}

Weinert, Howard L.; Kailath, Thomas. Stochastic Interpretations and Recursive Algorithms for Spline Functions. Ann. Statist., Tome 2 (1974) no. 1, pp.  787-794. http://gdmltest.u-ga.fr/item/1176342765/