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Hi, I have a cloud of randomly distributed points in 2-dimensional space and want to set up a grid, with a given grid-cell size, that minimizes the distance between my points and the grid nodes. Does anyone know of an R function or toolbox that somehow addresses this problem? This is a problem of optimizing the location of the grid, not a problem of deciding what should be the grid-cell size,

...r this data. Now i want to do k-nearest neighborhood classification by considering all the nearest neighbors of each station. i tried the following command to find neighbors of station 1, but first, it didn't work and second i would like to use my own distance matrix for the classification. >knnx.dist(X[-1,], X[1, , drop=FALSE], k=178) >knnx.index(X[-1,], X[1, , drop=FALSE], k=178) Thankyou very indeed in advance.Elisa [[alternative HTML version deleted]]