Page 59 - Basics of MATLAB and Beyond

load population.dat
year = population(:,1);
P = population(:,2);
plot(year,P,’:o’)
box;grid

The European population prior to 1850 was very low and we are unable
to see the fine detail. Detail is revealed when we use a logarithmic y-
scale:

semilogy(year,P,’:o’)
box;grid

The following functions implement logarithmic axes:

loglog Both axes logarithmic
semilogx logarithmic x-axis
semilogy logarithmic y-axis

14 Curve Fitting—Matrix Division

We continue with the example of Australian population data given in
the previous section. Let us see how well a polynomial fits this data. We
assume the data can be modelled by a parabola:
p = c 0 + c 1 x + c 2 x 2

where x is the year, c 0 , c 1 , and c 2 are coefficients to be found, and p is
the population. We write down this equation substituting our measured
data:

p 1 = c 0 + c 1 x 1 + c 2 x 2
1
p 2 = c 0 + c 1 x 2 + c 2 x 2
2
.
.
.
p N = c 0 + c 1 x N + c 2 x 2
N

c 2000 by CRC Press LLC