Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- Part I Matrix Methods
- Part II Numerical Methods
- Part III Least Squares and Optimization
- 10 Least-Squares Methods
- 11 Data Analysis: Curve Fitting and Interpolation
- 12 Optimization and Root Finding of Algebraic Systems
- 13 Data-Driven Methods and Reduced-Order Modeling
- References
- Index
11 - Data Analysis: Curve Fitting and Interpolation
from Part III - Least Squares and Optimization
Published online by Cambridge University Press: 18 February 2021
- Frontmatter
- Dedication
- Contents
- Preface
- Part I Matrix Methods
- Part II Numerical Methods
- Part III Least Squares and Optimization
- 10 Least-Squares Methods
- 11 Data Analysis: Curve Fitting and Interpolation
- 12 Optimization and Root Finding of Algebraic Systems
- 13 Data-Driven Methods and Reduced-Order Modeling
- References
- Index
Summary
Analysis of various data sets can be accomplished using techniques based on least-squares methods.For example, linear regression of data determines the best-fit line to the data via a least-squares approach.The same is true for polynomial and regression methods using other basis functions.Curve fitting is used to determine the best-fit line or curve to a particular set of data, while interpolation is used to determine a curve that passes through all of the data points.Polynomial and spline interpolation are discussed.State estimation is covered using techniques based on least-squares methods.
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- Publisher: Cambridge University PressPrint publication year: 2021