4: Least-Squares Approximation

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    4: Least-Squares Approximation

    The method of least-squares is commonly used to fit a parameterized curve to experimental data. In general, the fitting curve is not expected to pass through the data points, making this problem substantially different from the one of interpolation. We consider here only the simplest case of the same experimental error for all the data points. Let the data to be fitted be given by \(\left(x_{i}, y_{i}\right)\), with \(i=1\) to \(n\).


    This page titled 4: Least-Squares Approximation was last modified on Tue, 31 May 2022 07:52:02 GMT and is shared under a CC BY 1.0 license and was authored, remixed, and/or curated by Jeffrey R. Chasnov.