Confidence intervals for fit coefficients of cfit or
sfit object
ci = confint(fitresult)
ci = confint(fitresult,level)
ci = confint(fitresult) returns 95%
confidence bounds ci on the coefficients associated with the
cfit or sfit object
fitresult. fitresult must be an output
from the fit function to contain the
necessary information for ci. ci is a
2-by-n array where n =
numcoeffs(fitresult). The top row of ci contains
the lower bound for each coefficient; the bottom row contains the upper
bound.
ci = confint(fitresult,level) returns
confidence bounds at the confidence level specified by level.
level must be between 0 and
1. The default value of level is
0.95.
load census
fitresult = fit(cdate,pop,'poly2')
fitresult =
Linear model Poly2:
fitresult(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)
ci = confint(fitresult,0.95)
ci =
0.0061242 -25.086 19641
0.0069581 -21.934 22618Note that fit and confint display the
confidence bounds in slightly different formats.
To calculate confidence bounds, confint uses
R-1 (the inverse
R factor from QR decomposition of the
Jacobian), the degrees of freedom for error, and the root mean squared error. This
information is automatically returned by the fit function and
contained within fitresult.
If coefficients are bounded and one or more of the estimates are at their bounds, those estimates are regarded as fixed and do not have confidence bounds.
Note that you cannot calculate confidence bounds if
category(fitresult) is 'spline' or
'interpolant'.