User`s guide

2 Importing, Viewing, and Preprocessing Data
2-10
The Curve Fitting Toolbox supports these smoothing methods:
• Moving average filtering — Lowpass filter that takes the average of
neighboring data points.
• Lowess and loess — Locally weighted scatter plot smooth. These methods
use linear least squares fitting, and a first-degree polynomial (lowess) or a
second-degree polynomial (loess). Robust lowess and loess methods that are
resistant to outliers are also available.
• Savitzky-Golay filtering — A generalized moving average where you derive
the filter coefficients by performing an unweighted linear least squares fit
using a polynomial of the specified degree.
Note that you can also smooth data using a smoothing spline. Refer to
“Nonparametric Fitting” on page 3-68 for more information.
You smooth data with the Smooth pane of the Data GUI. The pane is shown
below followed by a description of its features.
Data sets
Data sets list
Smoothing method
and parameters