Data Fitting and Uncertainty

(A practical introduction to weighted least squares and beyond)

Tilo Strutz

Publisher: SpringerVieweg

2016: 2nd Edition (revised and extended)

ISBN-10: 365811455X
ISBN-13: 978-3-658-11455-8
Contents
Preface
Product Flyer
Erratum p.212

From the Author

New at least-squares approximation? Then give this textbook a try! You will find the solution for data-fitting problems in the beginning of the book. Linear and nonlinear problems are treated jointly. The more you want to learn, the deeper you have to dive into the book. You will find the theory behind the method of least squares as well as the details of modern numerical algorithms. Espacially the latter distinguishes "Data fitting and Uncertainty" from older texts. All discussed techniques rest on an implementation in working source code (ANSI-C), which is provided with the book.

From the Inside Flap

Among others, the book covers following topics
  • fitting of linear and non-linear functions with one- or multi-dimensional variables
  • weighted least squares
  • outlier detection
  • evaluation of the fitting results
  • different optimization strategies
  • combined fitting of different model functions
  • total least-squares approach with multi-dimensional conditions

From the Back Cover

The content:
  • Introduction to Data-Fitting Problems
  • Estimation of Model Parameters by Least Squares
  • Weights and Outliers
  • Uncertainty of Results
  • Matrix Algebra
  • The Idea Behind Least Squares
  • Supplemental Tools and Methods
Target Groups:
  • engineers, computer scientists, physicists and software programmers
  • undergraduates of engineering, computer science, physics

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Admin / 12.08.2016