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Curve Fitting Toolbox

Postprocessing Analysis

Once you have selected the curve or surface that best describes your data series you can perform postprocessing analysis. Curve Fitting Toolbox enables you to:

  • Create plots
  • Use your model to estimate values (evaluation)
  • Calculate confidence intervals
  • Create prediction bounds
  • Determine the area under your curve (integration)
  • Calculate derivatives
Postprocessing analysis with the Curve Fitting Tool.

Postprocessing analysis with the Curve Fitting app, which automatically creates a scatter plot of the raw data along with the fitted curve. The first and second derivatives of the fitted curve are also displayed.

The following examples show how postprocessing at the command line applies intuitive commands to the objects created from a fitting operation:

  • Evaluation: EnergyConsumption = fittedmodel(X, Y)
  • Plotting: EnergySurface = plot(fittedmodel)
  • Integration: Volume_Under_Surface = quad2d(fittedmodel, Min_X, Max_X, Min_Y, Max_Y)
  • Differentiation: Gradient = differentiate(fittedmodel, X,Y)
  • Computing confidence intervals: Confidence_Intervals = confint(fittedmodel)
Using command-line postprocessing to calculate and plot a gradient.

Using command-line postprocessing to calculate and plot a gradient.

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