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The classical Savitzky-Golay filter works only with uniformly sampled data and currently we have at least two good implementations of it for Mathematica published on our site. But in many practical situations we have to work with non-uniformly sampled data. This post states that it should not be too difficult to generalize the Savitzky-Golay filter for non-uniformly sampled data and describes the mathematical side of the problem shortly.

What is the best way to perform the non-uniform Savitzky-Golay smoothing and differentiation in Mathematica?

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    $\begingroup$ This is a bit difficult, since the underlying orthogonal polynomials are no longer as nice as the Gram polynomials. If memory serves, there is an algorithm due to Golub, Elhay, and Kautsky for this polynomial smoothing; you can try searching for it. $\endgroup$ – J. M. is away Jun 8 '15 at 14:16

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