MATLAB CURVE FITTING TOOLBOX - RELEASE NOTES Guide de l'utilisateur Page 167

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confint
4-91
Example Fit the census data to a second-degree polynomial. The display for fresult
includes the 95% confidence bounds for the fitted coefficients.
load census
fresult = fit(cdate,pop,'poly2')
fresult =
Linear model Poly2:
fresult(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)
Calculate 95% confidence bounds for the fitted coefficients using confint.
ci = confint(fresult,0.95)
ci =
0.0061242 -25.086 19641
0.0069581 -21.934 22618
Note that the fit display and the array returned by confint present the
confidence bounds using slightly different formats. The
fit display mimics an
n-by-3 array where n is the number of coefficients, the first column is the
coefficient variable, the second column is the fitted coefficient value, and the
third column is the lower and upper bound.
confint returns a 2-by-n array
where the top row contains the lower bound and the bottom row contains the
upper bound for each coefficient.
See Also fit
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