# Who can help me fit the data using the matlab, thank you.

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huazai2020 on 5 Aug 2020
Commented: Walter Roberson on 7 Sep 2020
Who can help me fit the data using the matlab, thank you.The fitting equation should be below:
y=b1*x1^b2 *x2^b3*x3^b4*x4^b5*x5^b6*x6^b7
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huazai2020 on 5 Aug 2020
These the data are just some part data from the whole data, the questions can be avoided if I put all the data, could you show me the code if I want to fit like this equation, thank you.

Ayush Gupta on 4 Sep 2020
Please refer to the following code on how to go about it and get the individual coefficients b1, b2, etc.
x1 = D(:,1);
x2 = D(:,2);
x3 = D(:,3);
x4 = D(:,4);
x5 = D(:,5);
x6 = D(:,6);
z = D(:,7);
x = [x1(:) x2(:) x3(:) x4(:) x5(:) x6(:)];
coeff = [ones(numel(z),1),log(x)]\log(z);
coeff (1) = exp(Coeff (1));
Walter Roberson on 7 Sep 2020
x = [x1(:) x2(:) x3(:) x4(:) x5(:) x6(:)];
Creates columns in an array, x. The first column is taken from x1, the second column is taken from x2, and so on.
coeff = [ones(numel(z),1),log(x)]\log(z);
The first part, ones(numel(z),1), creates a column of ones that is as long as z is (which in turn should be the same as the length of each of the x* variables.) So the left side of the \ creates an array in which the first column is all ones and the remaining columns are the logs of the x* variables.
The right side, log(z) is what it looks like, the log of the z variables.
The \ between the two asks for least squared fitting.
When you ask for least-squared fitting, then a column of ones corresponds to the constant term . The expression is finding the best values, coeff, such that
coeffs(1) + coeffs(2)*log(x1) + coeffs(3) + log(x2) + coeffs(4) * log(x3) + coeffs(5) * log(x4) + coeffs(6) * log(x5) + coeffs(7) * log(x6) fits log(z)
If you were to take exp() of this, it would be like
exp(coeffs(1)) * x1^coeffs(2) * x2^coeffs(3) * x3^coeffs(4) * x4^coeffs(5) * x5^coeffs(6) * x6^coeffs(7) fits z
and then
coeff (1) = exp(Coeff (1));
is converting the coeffs(1) that you got from the fitting to the exp(coeffs(1)) that you can see in the latter expression.