Curve Fitting Toolbox

disp

Display descriptive information for Curve Fitting Toolbox objects

Syntax

• obj
  disp(obj)
  

Arguments

obj	A Curve Fitting Toolbox object.

Description

obj or disp(obj) displays descriptive information for obj. You can create obj with the fit or cfit function, the fitoptions function, or the fittype function.

Example

The display for a custom fit type object is shown below.

• ftype = fittype('a*x^2+b*x+c+d*exp(-e*x)')
  
  ftype =
       General model:
         ftype(a,b,c,d,e,x) = a*x^2+b*x+c+d*exp(-e*x)
  

The display for a fit options object is shown below.

• fopts = fitoptions('Method','Nonlinear','Normalize','on')
  
  fopts =
          Normalize: 'on'
            Exclude: []
            Weights: []
             Method: 'NonlinearLeastSquares'
             Robust: 'Off'
         StartPoint: []
              Lower: []
              Upper: []
          Algorithm: 'Trust-Region'
      DiffMinChange: 1e-008
      DiffMaxChange: 0.1
            Display: 'Notify'
        MaxFunEvals: 600
            MaxIter: 400
             TolFun: 1e-006
               TolX: 1e-006
  

Note that all fit types have the Normalize, Exclude, Weights, and Method fit options. Additional fit options are available depending on the Method value. For example, if Method is SmoothingSpline, the SmoothingParam fit option is available.

The display for a fit result object is shown below.

• fresult = fit(cdate,pop,ftype,fopts)
  
  Warning: Start point not provided, choosing random start point.
  Maximum number of function evaluations exceeded. Increasing
  MaxFunEvals (in fit options) may allow for a better fit, or 
  the current equation may not be a good model for the data.
  
  fresult =
  
       General model:
         fresult(x) = a*x^2+b*x+c+d*exp(-e*x)
         where x is normalized by mean 1890 and std 62.05
       Coefficients (with 95% confidence bounds):
         a =       21.14  (-27.61, 69.89)
         b =       64.49  (-188.5, 317.4)
         c =       49.92  (-421.5, 521.4)
         d =       11.96  (-458, 481.9)
         e =     -0.7745  (-10.25, 8.701)
  

See Also

cfit, fit, fitoptions, fittype

differentiate

excludedata