Fast Compact Algorithms and Software for Spline Smoothing
By: by Howard L. Weinert
Contributors: SpringerLink (Online service)
Series: SpringerBriefs in Computer Science
Publisher: Springer New York; Imprint: Springer
Published: 2013
Place of publication: New York, NY
Language: eng
Format: [electronic resource] /
Number of pages: 45
ISBN-13: 9781461454960
Subjects: Statistics; Computer software; Appl.Mathematics/Computational Methods of Engineering; Mathematical statistics; Engineering mathematics; Computer science; Mathematical Software; Statistics and Computing/Statistics Programs; Image and Speech Processing Signal; Computational Science and Engineering
Description: <i>Fast Compact Algorithms and Software for Spline Smoothing</i> 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.
Table of contents: title: Introduction; title: Cholesky Algorithm; title: QR Algorithm; title: FFT Algorithm; title: Discrete Spline Smoothing.