Fast Compact Algorithms and Software for Spline Smoothing
Collection : SpringerBriefs in Computer Science, 2191-5768 Détails physiques : VIII, 45 p. 7 illus., 5 illus. in color. online resource. ISBN :9781461454960.
Sujet(s) :
Statistics.
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Computer mathematics.
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Computer software.
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Applied mathematics.
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Engineering mathematics.
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Statistics.
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Statistics and Computing/Statistics Programs.
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Signal, Image and Speech Processing.
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Computational Science and Engineering.
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Appl.Mathematics/Computational Methods of Engineering.
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Mathematical Software.
|
Computer mathematics.
|
Computer software.
|
Applied mathematics.
|
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.
Ressources en ligne :
Exemplaires : http://dx.doi.org/10.1007/978-1-4614-5496-0
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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