Fast Compact Algorithms and Software for Spline Smoothing - Info and Reading Options
By Howard L. Weinert
"Fast Compact Algorithms and Software for Spline Smoothing" was published by Springer New York in 2013 - New York, NY, it has 45 pages and the language of the book is English.
“Fast Compact Algorithms and Software for Spline Smoothing” Metadata:
- Title: ➤ Fast Compact Algorithms and Software for Spline Smoothing
- Author: Howard L. Weinert
- Language: English
- Number of Pages: 45
- Publisher: Springer New York
- Publish Date: 2013
- Publish Location: New York, NY
“Fast Compact Algorithms and Software for Spline Smoothing” Subjects and Themes:
- 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
Edition Specifications:
- Format: [electronic resource] /
- Pagination: ➤ VIII, 45 p. 7 illus., 5 illus. in color.
Edition Identifiers:
- The Open Library ID: OL27038231M - OL19849505W
- ISBN-13: 9781461454960 - 9781283908016
- All ISBNs: 9781461454960 - 9781283908016
AI-generated Review of “Fast Compact Algorithms and Software for Spline Smoothing”:
"Fast Compact Algorithms and Software for Spline Smoothing" Table Of Contents:
- 1- Introduction
- 2- Cholesky Algorithm
- 3- QR Algorithm
- 4- FFT Algorithm
- 5- Discrete Spline Smoothing.
"Fast Compact Algorithms and Software for Spline Smoothing" Description:
The Open Library:
<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.
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