MATLAB CURVE FITTING TOOLBOX - RELEASE NOTES Podręcznik Użytkownika Strona 28

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1 Getting Started with the Curve Fitting Toolbox
1-14
The cfit object display includes the model, the fitted coefficients, and the
confidence bounds for the fitted coefficients.
fittedmodel1
fittedmodel1 =
Linear model Poly2:
fittedmodel1(x) = p1*x^2 + p2*x + p3
Coefficients (with 95% confidence bounds):
p1 = 0.006541 (0.006124, 0.006958)
p2 = -23.51 (-25.09, -21.93)
p3 = 2.113e+004 (1.964e+004, 2.262e+004)
The goodness1 structure contains goodness of fit results.
goodness1
goodness1 =
sse: 159.0293
rsquare: 0.9987
dfe: 18
adjrsquare: 0.9986
rmse: 2.9724
The output1 structure contains additional information associated with the fit.
output1
output1 =
numobs: 21
numparam: 3
residuals: [21x1 double]
Jacobian: [21x3 double]
exitflag: 1
algorithm: 'QR factorization and solve'
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