MATLAB CURVE FITTING TOOLBOX - RELEASE NOTES Guide de l'utilisateur Page 149

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Nonparametric Fitting
3-73
As shown below, you can fit the data with a smoothing spline by selecting
Smoothing Spline in the Type of fit list.
The level of smoothness is given by the
Smoothing Parameter. The default
smoothing parameter value depends on the data set, and is automatically
calculated by the toolbox after you click the
Apply button.
For this data set, the default smoothing parameter is close to 1, indicating that
the smoothing spline is nearly cubic and comes very close to passing through
each data point. Create a fit for the default smoothing parameter and name it
Smooth1. If you do not like the level of smoothing produced by the default
smoothing parameter, you can specify any value between 0 and 1. A value of 0
produces a piecewise linear polynomial fit, while a value of 1 produces a
piecewise cubic polynomial fit, which passes through all the data points. For
comparison purposes, create another smoothing spline fit using a smoothing
parameter of 0.5 and name the fit
Smooth2.
The numerical results for the smoothing spline fit
Smooth1 are shown below.
The default smoothing
parameter is based on
the data set you fit.
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