- polydern
- polyfitn
- polyn2sym
- polyn2sympoly
- polyvain
Multiple input vector for polyfit and get polyval , derive the best coeff & least RMS Error
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Hi
I have a code which is computing the polyval for multiple input vectors. I would like to derive best coefficient and lowest RMS error
Does MATLAB offer a manner in which I can fit all (x input number) of these simultaneously, where the solution is in the form of a polynomial, and will have some fitted coefficients/best, so that each curve is fit properly?
x1 = rand(12,1); % or replacec with a know data 1:10
x2 = rand(12,1); % or replacec with a know data 2:11
x3 = rand(12,1); % or replacec with a know data 3:12
x4 = rand(12,1); % or replacec with a know data 4:13
x5 = rand(12,1); % or replacec with a know data 5:14
x6 = rand(12,1); % or replacec with a know data 6:15
x7 = rand(12,1); % or replacec with a know data 7:16
x8 = rand(12,1); % or replacec with a know data 8:17
X = [x1,x2,x3,x4,x5,x6,x7,x8];
for n = 1:7
[p,S,mu] = polyfit(X(n),X(n+1),4) % polynomial order [ 2-4]
f(n)= polyval(p,X(n));
plot(X(n),X(n+1),'-o',X(n),f(n),'-+'); hold on;grid on
legend('data','linear fit')
end
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Réponses (1)
Rishabh Mishra
le 7 Jan 2021
Hi,
Try using the following MATLAB functions for curve fitting & creating polynomials from the given data.
The documentation of above functions is available in MATLAB file exchange. Just type ‘doc functionName’ in your MATLAB console where functionName is any of the above functions.
Feel free to reach out if you are still facing problems while resolving the issue.
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Life is Wonderful
le 8 Jan 2021
Modifié(e) : Life is Wonderful
le 8 Jan 2021
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