Fast Compact Algorithms and Software for Spline Smoothing
Weinert, Howard L.
Fast Compact Algorithms and Software for Spline Smoothing [electronic resource] / by Howard L. Weinert. - VIII, 45 p. 7 illus., 5 illus. in color. online resource. - SpringerBriefs in Computer Science, 2191-5768 . - SpringerBriefs in Computer Science, .
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.
9781461454960
10.1007/978-1-4614-5496-0 doi
Statistics.
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.
QA276-280
519.5
Fast Compact Algorithms and Software for Spline Smoothing [electronic resource] / by Howard L. Weinert. - VIII, 45 p. 7 illus., 5 illus. in color. online resource. - SpringerBriefs in Computer Science, 2191-5768 . - SpringerBriefs in Computer Science, .
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.
9781461454960
10.1007/978-1-4614-5496-0 doi
Statistics.
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.
QA276-280
519.5