Is it possible to use Matlab to get expressions for the coefficients in polynomial regression? (I.e., not just constant coefficients)
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Srh Fwl
el 25 de Mayo de 2022
I'm trying to modify one section of an old code so that it uses my new data for one of its parameters. The code expresses an equation as a fourth-order power series in X and y. I know how to do polynomial regression on a curve like the one below to get an expression like:
Phi=k0+k1y+k2y2+k3y3+k4y4
However, my problem is that the code uses a more sophisticated expression for k. I.e.,
I need to express the k this way (in terms of a coefficients) because they're needed elsewhere in the code. Right now, the a coefficients are provided in a table in the code, but I have no idea how to calculate them.
I'm comfortable using Matlab and would be grateful if someone could tell me whether there is a way to do polynomial regression for a fourth-order power series (based on curves like the one in the top figure above) and get the coefficients in terms of a coefficients as shown in the figure above. I have looked around but it does not seem like it is possible. For example "multiple linear regression" and "multivariate regression" don't seem to do what I need. Maybe they do though and I'm not experienced enough to see it? Thank you for any advice.
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Torsten
el 25 de Mayo de 2022
So X and Y are independent variables and phi = f(X,Y) ?
I ask this because in your ansatz for phi
phi = k0 + k1*Y + k2*Y^2 + k3*Y^3 + k4*Y^4
X as variable does not appear.
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Torsten
el 25 de Mayo de 2022
M = [X.^(-1).*Y,X.^(-1).*Y.^2,Y.^2,X.*Y.^2,X.^(-1).*Y.^3,X.*Y.^3,X.^2.*Y.^3,X.^(-2).*Y.^4,X.^(-1).*Y.^4,Y.^4];
b = PHI - 1.0;
a = M\b;
where X,Y and PHI are column vectors of the same size.
Here, a(i) = ai in your problem description.
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Torsten
el 26 de Mayo de 2022
It makes sense that the a coefficients are going to be in the form of a vector, but I'm hung up on what Bruno has done to get his "M = " expression.
M*a = b
written out gives
x^(-1)*y*a(1)+x^(-1)*y^2*a(2)+y^2*a(3)+x*y^2*a(4) ... = PHI - 1
thus your model function equation.
You want to solve this equation for a, thus
a = M\b
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Walter Roberson
el 25 de Mayo de 2022
For each equation divide both sides by the highest negative coefficient,
k4(Xhat)/Xhat^(-2) = a8*Xhat^(-2)/Xhat^(-2) + etc
k4(Xhat)*Xhat^2 = a8 + a9*Xhat + a10*Xhat^2
subtract left from right and you have a standard polynomial that you can do fitting on
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