The approximation power of moving least-squares

@article{Lev98, abstract = {. A general method for near-best approximations to functionals on IR d , using scattered-data information is discussed. The method is actually the moving least-squares method, presented by the Backus-Gilbert approach. It is shown that the method works very well for interpolation, smoothing and derivatives' approximations. For the interpolation problem this approach gives Mclain's method. The method is near-best in the sense that the local error is bounded in terms of the error of a local best ...}, author = {Levin, David }, citeulike-article-id = {1525873}, journal = {Mathematics of Computation}, keywords = {approximation}, number = {224}, pages = {1517--1531}, posted-at = {2008-07-14 16:01:25}, priority = {2}, title = {The approximation power of moving least-squares}, url = {http://citeseer.ist.psu.edu/levin98approximation.html}, volume = {67}, year = {1998} }

TY - JOUR ID - Lev98 L3 - citeulike-article-id:1525873 TI - The approximation power of moving least-squares JF - Mathematics of Computation VL - 67 IS - 224 SP - 1517 EP - 1531 N2 - . A general method for near-best approximations to functionals on IR d , using scattered-data information is discussed. The method is actually the moving least-squares method, presented by the Backus-Gilbert approach. It is shown that the method works very well for interpolation, smoothing and derivatives' approximations. For the interpolation problem this approach gives Mclain's method. The method is near-best in the sense that the local error is bounded in terms of the error of a local best ... KW - approximation AU - Levin, David PY - 1998/// UR - http://citeseer.ist.psu.edu/levin98approximation.html ER -