Stable moving least-squares
Local polynomial fitting in a least squares sense is a common technique in scattered data approximation. However, some known error bounds indicate that the error may become rather large for certain configurations of the given data points. In this paper, the author proves that these bounds are indeed realistic and proposes a modified technique, called stable moving least squares, that leads to better bounds in such worst-case situations.
scientific article; zbMATH DE number 5639050