Curve Fitting Toolbox
Product Description
- Introduction and Key Features
- Working with Curve Fitting Toolbox
- Regression
- Splines and Interpolation
- Smoothing
- Previewing and Preprocessing Data
- Developing, Comparing, and Managing Models
- Postprocessing Analysis
Splines and Interpolation
Curve Fitting Toolbox supports a variety of interpolation methods, including B-splines, thin plate splines, and tensor product splines. Curve Fitting Toolbox provides functions for advanced spline operations, including break/knot manipulation, optimal knot placement, and data-point weighting.
A cubic B-spline and the four polynomials from which it is made. Splines are smooth piecewise polynomials used to represent functions over large intervals.
You can represent a polynomial spline in ppform and B-form. The ppform describes the spline in terms of breakpoints and local polynomial coefficients, and is useful when the spline will be evaluated extensively. The B-form describes a spline as a linear combination of B-splines, specifically the knot sequence and B-spline coefficients.
Curve Fitting Toolbox also supports other types of interpolation, including:
- Linear interpolation
- Nearest neighbor interpolation
- Piecewise cubic interpolation
- Biharmonic surface interpolation
- Piecewise Cubic Hermite Interpolating Polynomial (PCHIP)
The Curve Fitting Toolbox commands for constructing spline approximations accommodate vector-valued gridded data, enabling you to create curve and surfaces in any number of dimensions.

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