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smoothing -凯发k8网页登录

fit using smoothing splines and localized regression, smooth data with moving average and other filters

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 function. for an example showing how to smooth data, see fit smooth surfaces to investigate fuel efficiency.

apps

curve fitterfit curves and surfaces to data

functions

data statistics
exclude data from fit
fitfit 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

topics


  • fit smoothing splines in the curve fitter app or with the fit function to create a smooth curve through data and specify the smoothness.


  • fit smooth surfaces to your data in the curve fitter app or with the fit function using lowess models.


  • 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 and rloess).

  • 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.


  • perform nonparametric fitting to create smooth curves or surfaces through your data with interpolants and smoothing splines.

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