16: Interpolation and Curve Fitting
- Page ID
- 98979
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- 16.1: Linear Interpolation
- Linear interpolation estimates values of a relationship between elements of the given values.
- 16.2: Nonlinear Interpolation
- Spline and pchip interpolation give smooth curves.
- 16.3: Regression Analysis
- Suppose we calculate some variable of interest, y, as a function of some other variable x. We call y the dependent variable and x the independent variable. For example, consider the data set below, taken from a simple experiment involving a vehicle, its velocity versus time is tabulated. In this case, velocity is a function of time, thus velocity is the dependent variable and the time is the independent variable.
- 16.4: Linear Data Fitting and Interpolation
- A relationship between x and y variables may be expected to be approximately linear. But a measured data may have measurement errors or there may be some minor non-linear effects. You can find the best linear fit to the data with the commands in this section: polyfit, polyval and interp1.
- 16.5: Higher Order Polynomial Fitting
- Curve fitting using polynomials.
- 16.6: Interactive Fitting Tools
- Interactive tools use menu items on a figure.
- 16.7: Chapter 16 Videos in English and Espanol
- Chapter videos