Smoothing
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 theCurve Fitter应用程序或在命令行上我们ing thesmooth
function. For an example showing how to smooth data, seeFit Smooth Surfaces to Investigate Fuel Efficiency.
Apps
Curve Fitter | Fit curves and surfaces to data |
Functions
datastats |
Data statistics |
excludedata |
Exclude data from fit |
fit |
Fit curve or surface to data |
fittype |
Fit type for curve and surface fitting |
fitoptions |
Create or modify fit options object |
get |
Get fit options structure property names and values |
set |
Assign values in fit options structure |
smooth |
平滑的响应数据 |
prepareCurveData |
Prepare data inputs for curve fitting |
prepareSurfaceData |
Prepare data inputs for surface fitting |
Topics
- Smoothing Splines
Fit smoothing splines in the Curve Fitter app or with the
fit
function 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
fit
function using Lowess models. - Filtering and Smoothing Data
Use the
smooth
function to smooth response data, using methods for moving average, Savitzky-Golay filters, and local regression with and without weights and robustness (lowess
,loess
,rlowess
andrloess
). - 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.