MATLAB POLYSPACE RELEASE NOTES User Manual Page 190

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5 Data Analysis
The model has the advantage of being simple while following the up-and-down
trend. The accuracy of its predictive power, however, is questionable,
especially at the ends of the data.
General Linear Regression
Assuming that the data are periodic with a 1 2-hour period and a peak around
hour 7, it is reasonable to fit a sinusoidal model of the form:
yab t=+ cos(( / )( ))212 7π
The coefficients a and b appear linearly. Use the MATLAB ml divide
(backslash) operator to fit general linear models:
c3 = count(:,3); % Data at intersection 3
tdata = (1:24)';
5-20
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