[Numpy-discussion] performance issue (again)
josef.pktd@gmai...
josef.pktd@gmai...
Wed Apr 22 11:38:32 CDT 2009
On Wed, Apr 22, 2009 at 11:48 AM, Mathew Yeates <myeates@jpl.nasa.gov>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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