On Wed, Apr 22, 2009 at 11:48 AM, Mathew Yeates <[email protected]>wrote:
> well, this isn't a perfect solution. polyfit is better because it > determines rank based on condition values. Finds the eigenvalues ... > etc. But, unless it can vectorized without Python looping, it's too slow > for me to use > rank is a property of the design matrix. In your case the design matrix is a vector of ones and the x vector. So the only case, where you run into problems, is when your three observation of x are the same, then dot(x.T*x) is zero, you can only have one constant. If there is no slope in x then you don't have three different observations to estimate a slope coefficient. Just special case (x*x).sum(1)<1e-8 or something, in this case yestimate = y.mean eigen vectors with one regressor are pretty useless or trivial, same with rank. For higher order polynomials this will become more important, but not for a linear polynomial. Josef
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