How do I fit an exponential equation to raw data
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I have been given raw data from a hurricane with the x component, radius, x=59:803 and Y component, pressure, data varying from around 990 to 1020. I have an equaiton y=exp(-A/(x^B)) and want to find coefficients A and B from the raw data. I did try applying fit and to no avail. I'm unfamiliar with these functions so perhaps I was using them incorrectly.
I hope you can help, Thanks.
PH
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Accepted Answer
Jos (10584)
on 18 Feb 2018
Edited: Jos (10584)
on 19 Feb 2018
This should get you started:
% some data
x = 1:20 ;
y = exp(-10 ./ (x .^ 1.1)) ;
yr = y + randn(size(y))/10 ; % add noise
% fit procedure
g = fittype(@(A,B,x) exp(-A ./ (x.^B)))
f = fit(x(:),yr(:), g )
% result
yh = f(x) ;
plot(x,yr,'bo',x,y,'b:.',x,yh,'rs-')
For more information, read the documentation on fit.
3 Comments
Jos (10584)
on 19 Feb 2018
What is the exact error you get?
(btw I made a mistake in my function, which I fixed)
More Answers (1)
Star Strider
on 18 Feb 2018
You can use the fminsearch function to do the nonlinear regression.
The Code —
P = load('pressure.mat.txt');
R = load('radius.mat.txt');
Pressmb = P.Pressmb;
Radkm = R.Radkm;
PresRad = @(b,r) exp(-b(1)./(r.^b(2))); % Objective Function
B = fminsearch(@(b) norm(Pressmb - PresRad(b,Radkm)), [1, 1]);
RadV = linspace(min(Radkm), max(Radkm));
figure
plot(Radkm, Pressmb, 'pg')
hold on
plot(RadV, PresRad(B, RadV), '-r')
hold off
xlabel('Radius (km)')
ylabel('Pressure (mb)')
legend('Data', 'Fitted Data', 'Location','NW')
text(440, 997, sprintf('P(R) = e^{%.2f/(%.5f\\cdotR)}',B))
grid
The Plot —
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