I'm programming an n-dimensional polynomial fitting function. It uses the basic concept of least squares and a design matrix.
For example, a quadratic fit on 2d data:
This is a row in the design Matrix:
$X={({1, x, x^2})}$
And this is the matrix formula I'm using:
$(X^T*X)^{-1}(X^T*Y)=Ax^2+Bx+C$
This is nothing special or complicated.
I'm at the point however where I'd like to introduce confidence intervals. How do I compute the confidence intervals from this regression technique?
No comments:
Post a Comment