How to find a linear approximation on loglog scale?
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Nimrod Daniel
on 17 Jan 2014
Commented: Nimrod Daniel
on 17 Jan 2014
Hello,
I have two data vectors and a loglog plot of a frequency as a function of mass, and I want to do a linear approximation on the loglog scale.
mass=[8.55 3.08 3.24 1.23 0.418 0.155 0.035 0.122 0.133 2.23 1.69 0.89 0.61 0.437 8.5];
frequency= [2.49 2.97 3.14 3.93 5.61 5.42 7.65 12.3 12.3 5.85 3.95 3.46 6.35 7.62 3.56];
loglog(freq,mass,'.b');
I tried using the basic fitting tool, but I'm not getting a linear approx. on the loglog plot. Maybe polyfit could help here ? how do I do the linear approx. in the loglog scale case ?
Thanks :)
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Accepted Answer
Mischa Kim
on 17 Jan 2014
Hello Daniel, you could log your data before doing the curve fit and take it from there.
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Mischa Kim
on 17 Jan 2014
freq= [2.49 2.97 3.14 3.93 5.61 5.42 7.65 12.3 12.3 5.85 3.95 3.46 6.35 7.62 3.56];
mass=[8.55 3.08 3.24 1.23 0.418 0.155 0.035 0.122 0.133 2.23 1.69 0.89 0.61 0.437 8.5];
loglog(freq,mass,'.b');
lfreq = log(freq);
lmass = log(mass);
p = polyfit(lfreq, lmass, 1);
x_fitlin = linspace(0,4,2);
y_fitlin = p(1)*x_fitlin + p(2);
x_fitlog = exp(x_fitlin);
y_fitlog = exp(y_fitlin);
hold on
plot(x_fitlog,y_fitlog,'r')
Is that what you are looking for? First, log the data, then do the curve fit. In this case a polynomial of degree 1 (linear approx.). Once you have the coefficients you need to un-do the log, that's where the exp comes into play.
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