16: Interpolation and Curve Fitting
- Page ID
- 84347
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- 16.1: Linear Interpolation
- Linear interpolation is one of the most common techniques for estimating values between two given data points. For example, when using steam tables, we often have to carry out interpolations. The simplest method is linear interpolation. With this technique, we assume that the function between the two points is linear. MATLAB has a built-in linear interpolation function. It also has options for spline and pchip interpolation.
- 16.2: Nonlinear Interpolation
- Spline and pchip interpolation give smooth curves.
- 16.3: Linear Data Fitting and Interpolation
- The main commands for this section are polyfit, polyval and interp1.
- 16.5: 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.
- 16.6: Interactive Fitting Tools
- Interactive tools use menu items on a figure.