Create splines including B-form, tensor-product,
NURBs and other rational splines

`bspline` |
Plot B-spline and its polynomial pieces |

`csape` |
Cubic spline interpolation with end conditions |

`csapi` |
Cubic spline interpolation |

`csaps` |
Cubic smoothing spline |

`cscvn` |
"Natural" or periodic interpolating cubic spline curve |

`getcurve` |
Interactive creation of cubic spline curve |

`ppmak` |
Put together spline in ppform |

`rpmak` |
Put together rational spline |

`rscvn` |
Piecewise biarc Hermite interpolation |

`rsmak` |
Put together rational spline for standard geometric shapes |

`spap2` |
Least-squares spline approximation |

`spapi` |
Spline interpolation |

`spaps` |
Smoothing spline |

`spcrv` |
Spline curve by uniform subdivision |

`splinetool` |
Experiment with some spline approximation methods |

`spmak` |
Put together spline in B-form |

`stmak` |
Put together function in stform |

`tpaps` |
Thin-plate smoothing spline |

Use cubic splines to interpolate smooth data, choosing knots and smoothness.

Use vector-valued splines to plot curves through given points.

**Fitting Values at N-D Grid with Tensor-Product Splines**

Use vector-valued splines to approximate gridded data in any number of variables using tensor-product splines.

**Fitting Values at Scattered 2-D Sites with Thin-Plate Smoothing
Splines**

Use the thin-plate smoothing spline for work with scattered bivariate data. Tensor-product splines are good for gridded (bivariate and even multivariate) data.

**Constructing and Working with ppform Splines**

Learn how to construct ppform splines.

**Constructing and Working with B-form Splines**

Learn how to construct B-form splines.

**Multivariate Tensor Product Splines**

Learn how to construct multivariate splines.

**Constructing and Working with Rational Splines**

Learn how to construct rational splines.

**Constructing and Working with stform Splines**

Learn how to construct stform splines.

**Least-Squares Approximation by Natural Cubic Splines**

The construction of a least-squares approximant usually requires that one have in hand a basis for the space from which the data are to be approximated.

This section discusses these aspects of a nonlinear ODE problem:

**Construction of the Chebyshev Spline**

This section discusses these aspects of the Chebyshev spline construction:

**Approximation by Tensor Product Splines**

Because the toolbox can handle splines with *vector* coefficients,
it is easy to implement interpolation or approximation to gridded data by tensor product splines, as the following illustration is meant to show.

Tools for interactive and programmatic spline fitting in Curve Fitting Toolbox™.

**Curve Fitting Toolbox Splines and MATLAB Splines**

How Curve Fitting Toolbox extends the splines (or
piecewise-polynomial functions) of MATLAB^{®}.

**Types of Splines: ppform and B-form**

Learn about the definitions of the ppform and B-form splines.

**B-Splines and Smoothing Splines**

Learn about the definitions of the B-form and smoothing splines.

**Multivariate and Rational Splines**

Learn how to construct multivariate and rational splines.

Learn about the definition of the ppform spline.

Learn about the definition of B-form splines.

**List of Terms for Spline Fitting**

Terms and definitions presented in order such that the explanation of each term only uses terms discussed earlier

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