Fast Compact Algorithms and Software for Spline Smoothing, 2013 SpringerBriefs in Computer Science Series
Langue : Anglais
Auteur : Weinert Howard L.
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.
Introduction.- Cholesky Algorithm.- QR Algorithm.- FFT Algorithm.- Discrete Spline Smoothing.
Date de parution : 10-2012
Ouvrage de 45 p.
15.5x23.5 cm
Thèmes de Fast Compact Algorithms and Software for Spline Smoothing :
Mots-clés :
Cross-validation; Graduation; Interpolation; Smoothing; Spline
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