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Newton polynomial
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==Addition of new points== As with other difference formulas, the degree of a Newton interpolating polynomial can be increased by adding more terms and points without discarding existing ones. Newton's form has the simplicity that the new points are always added at one end: Newton's forward formula can add new points to the right, and Newton's backward formula can add new points to the left. The accuracy of polynomial interpolation depends on how close the interpolated point is to the middle of the ''x'' values of the set of points used. Obviously, as new points are added at one end, that middle becomes farther and farther from the first data point. Therefore, if it isn't known how many points will be needed for the desired accuracy, the middle of the x-values might be far from where the interpolation is done. Gauss, Stirling, and Bessel all developed formulae to remedy that problem.<ref>{{Cite book |last=Hamming |first=Richard W. |title=Numerical methods for scientists and engineers |date=1986 |publisher=Dover |isbn=978-0-486-65241-2 |edition=Unabridged republ. of the 2. ed. (1973) |location=New York}}</ref> Gauss's formula alternately adds new points at the left and right ends, thereby keeping the set of points centered near the same place (near the evaluated point). When so doing, it uses terms from Newton's formula, with data points and ''x'' values renamed in keeping with one's choice of what data point is designated as the ''x''<sub>0</sub> data point. Stirling's formula remains centered about a particular data point, for use when the evaluated point is nearer to a data point than to a middle of two data points. Bessel's formula remains centered about a particular middle between two data points, for use when the evaluated point is nearer to a middle than to a data point. Bessel and Stirling achieve that by sometimes using the average of two differences, and sometimes using the average of two products of binomials in ''x'', where Newton's or Gauss's would use just one difference or product. Stirling's uses an average difference in odd-degree terms (whose difference uses an even number of data points); Bessel's uses an average difference in even-degree terms (whose difference uses an odd number of data points).
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