In the last two columns, we looked at one approach to approximation, interpolating a set of points by piecewise-cubic polynomials forming a cubic spline. We now look at another approach - one that involves fitting a curve to a set of data without restricting that curve to coincide with the data points. Our focus is on least-squares approximation, and, in particular, least-square fitting of polynomials to data.
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Dyer et al. (2001) studied this question.