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Fast Compact Algorithms and Software for Spline Smoothing

by Weinert, Howard L.
Authors: SpringerLink (Online service) Series: SpringerBriefs in Computer Science, 2191-5768 Physical details: VIII, 45 p. 7 illus., 5 illus. in color. online resource. ISBN: 1461454964 Subject(s): Statistics. | Computer science. | Computer software. | Mathematical statistics. | Engineering mathematics. | Statistics. | Statistics and Computing/Statistics Programs. | Signal, Image and Speech Processing. | Computational Science and Engineering. | Appl.Mathematics/Computational Methods of Engineering. | Mathematical Software.
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E-Book E-Book AUM Main Library 519.5 (Browse Shelf) Not for loan

Introduction -- Cholesky Algorithm -- QR Algorithm -- FFT Algorithm -- Discrete Spline Smoothing.

Fast Compact Algorithms and Software for Spline Smoothing investigates algorithmic alternatives for computing cubic smoothing splines when the amount of smoothing is determined automatically by minimizing the generalized cross-validation score. These algorithms are based on Cholesky factorization, QR factorization, or the fast Fourier transform. All algorithms are implemented in MATLAB and are compared based on speed, memory use, and accuracy. An overall best algorithm is identified, which allows very large data sets to be processed quickly on a personal computer.

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