Curve Fitting Toolbox | ![]() ![]() |
Display descriptive information for Curve Fitting Toolbox objects
Syntax
Arguments
obj |
A Curve Fitting Toolbox object. |
Description
or obj
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
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