Smoothing is a method of reducing the noise within a data set. Curve Fitting Toolbox™ allows you to smooth data using methods such as moving average, Savitzky-Golay filter and Lowess models or by fitting a smoothing spline.
Smooth data interactively using the Curve Fitter app or at the
command line using the
smooth function. For an
example showing how to smooth data, see Fit Smooth Surfaces to Investigate Fuel Efficiency.
|Curve Fitter||Fit curves and surfaces to data|
|Exclude data from fit|
|Fit curve or surface to data|
|Fit type for curve and surface fitting|
|Create or modify fit options object|
|Get fit options structure property names and values|
|Assign values in fit options structure|
|Smooth response data|
|Prepare data inputs for curve fitting|
|Prepare data inputs for surface fitting|
- Smoothing Splines
Fit smoothing splines in the Curve Fitter app or with the
fitfunction to create a smooth curve through data and specify the smoothness.
- Lowess Smoothing
Fit smooth surfaces to your data in the Curve Fitter app or with the
fitfunction using Lowess models.
- Filtering and Smoothing Data
smoothfunction to smooth response data, using methods for moving average, Savitzky-Golay filters, and local regression with and without weights and robustness (
- Fit Smooth Surfaces to Investigate Fuel Efficiency
This example shows how to use Curve Fitting Toolbox™ to fit a response surface to some automotive data to investigate fuel efficiency.
- Nonparametric Fitting
Perform nonparametric fitting to create smooth curves or surfaces through your data with interpolants and smoothing splines.