Hi all, when making a polynomial fit on a data set with n points it should always be possible to find a n-1 degree polynomial expression that gives a mean squared error equal to 0 (well, rounding errors make this an 'almost' 0) When using the SVD algoritm in the General Plynomial Fit.vi this isn't always the case. Is this due to the qualities of the SVD algorithm ? E.g. the Givens algorithm seems more stable. My math is a little rusty so I'll appreciate comments from you math-gurus that I know reside out there.
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