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Fast Compact Algorithms and Software for Spline Smoothing

  • Howard L.¬†Weinert

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Howard L. Weinert
    Pages 1-4
  3. Howard L. Weinert
    Pages 5-18
  4. Howard L. Weinert
    Pages 19-28
  5. Howard L. Weinert
    Pages 29-35
  6. Howard L. Weinert
    Pages 37-45

About this book

Introduction

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.

Keywords

Cross-validation Graduation Interpolation Smoothing Spline

Authors and affiliations

  • Howard L.¬†Weinert
    • 1
  1. 1., Department of Electrical andJohns Hopkins UniversityBALTIMOREUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-5496-0
  • Copyright Information The Author(s) 2013
  • Publisher Name Springer, New York, NY
  • eBook Packages Computer Science
  • Print ISBN 978-1-4614-5495-3
  • Online ISBN 978-1-4614-5496-0
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • Buy this book on publisher's site
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