CODEWITHSUNDEEP
matlableast-squares
rphello101
rphello101

Reputation: 1771

In Matlab, how do you mathematically get a quadratic line of best fit?

I'm having trouble getting a quadratic line of best fit in Matlab. We aren't allowed to use the built-in line of best fit functions, but instead have to calculate it. This is what I have:

dat = load('co2.dat');
x = dat(:,1);
y = dat(:,2);
X = [ones(size(x)),x.^2];
z = X'*y;
S = X'*X;
U = chol(S);
w = U'\z;
c = U\w
axis tight;
plot(x,y,'o') 
q = 1959:2:2012; 
fit = c(1)+c(2)*q; 
hold on
plot(q,fit,'r');

This just draws a horizontal line at -1000. If I get rid of the .^2 in the 4th line, it does a linear fit perfectly. Perhaps my problem rests more in my lack of knowledge with least squares than with Matlab, but, either way, I'm stumped (advise if this should be moved to the math forum). Any advice?

Upvotes: 0

Views: 573

Answers (1)

lennon310
lennon310

Reputation: 12689

I changed two lines of yours:

X=[ones(size(x)), x, x.^2];

and,

fit = c(1)+c(2)*q+c(3)*q.^2;

Please have a try, thx.

Upvotes: 2

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