fitting data with power function
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Hi,
I need to curve fit to data, which i had meassured. I must use method of least squares and for fitting i must use a „power function“ y= a*x^b ((ftype=fittype('power1')); I need to find the coefficients a and b. But i dont know how to do in Matlab, i try to write some m-scripts but it doesnt works.
Example of meassured data:
X=[-90; -80; -70; -60; -50; -40; -30; -20; -10;0; 10; 20; 30; 40; 50;60; 70; 80; 90]
Y=[-2.8691; -2.4261; -2.0042; -1.7497; -1.3936; -1.1392; -0.9356; -0.7321; -0.5286; 0; 0.3872; 0.6416; 0.8451; 1.0995; 1.3031; 1.6083;1.9136; 2.3207; 2.524]
I will be grateful for any idea or any help. Thank you very much.
1 Comment
safak
on 8 Apr 2018
did you check the command window, coefficients may be printed out there
Answers (3)
bym
on 26 Jun 2011
Plotting your data it does not seem to fit a power function and seems linear. You can use the backslash operator to do least squares
doc mldivide
or in the plot window, use tools>basic fitting to fit a linear equation
4 Comments
Jana
on 27 Jun 2011
bym
on 27 Jun 2011
you can use the backslash to find the coefficients, you will just have to transform your data using logarithms.
Jana
on 27 Jun 2011
bym
on 27 Jun 2011
if you have zeros in your data, then maybe a different approach is warranted. If you can post some 'real' data then maybe a solution can be found
Jana
on 28 Jun 2011
Edited: Walter Roberson
on 8 Apr 2018
Matt Fig
on 28 Jun 2011
If I use this data and plot as you show, it looks near linear. Why would you think this should be a power law relation?
x=[-90; -80; -70; -60; -50; -40; -30; -20; -10; 10; 20; 30; 40; 50;60; 70; 80; 90]';
y=[-2.8691; -2.4261; -2.0042; -1.7497; -1.3936; -1.1392; -0.9356; -0.7321; -0.5286; 0.3872; 0.6416; 0.8451; 1.0995; 1.3031; 1.6083;1.9136; 2.3207; 2.524]';
plot(x,y,'r-*')
pp = polyfit(x,y,1); % Fit a line to the data
yp = polyval(pp,x);
hold on
plot(x,yp,'b') % Plot the line in blue.
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