Before revision:  With both s-resistars and m-resistars, classifying a point  requires only a small number  of simple tests without explicitly computing the simplices. It is thus possible to use resistar classification in spaces of relatively high dimensionality (up to 9 in our tests) and for resistar surfaces including a large number of simplices (up to several trillions in our tests). The paper provides a theoretical argument and empirical evidence suggesting that, when the surface to approximate is smooth enough, the error of resistar classification decreases as \mathcal{O n_G^{-2}) for a grid of size n_G^d in d dimensions, whereas this error decreases as \mathcal{O .
After revision:  With both s-resistars and m-resistars, classifying a point requires only a small number of simple tests . Under some conditions on the definition of the boundary points and on the reach of M, for both variants the Hausdorff distance between M and its approximation decreases like \mathcal{O n_G^{-2}) for a grid of size n_G^d in d dimensions, whereas this error decreases as \mathcal{O .