Hello all, Allin & Jack ! You really saved my day ! Let me sum up the situation. I tested both scripts, they run perfectly ! In fact the msortby command is not documented yet, this is why i had trouble to translate the find_nn command of James Lesage. Now I can compute the right neighborhood matrices from a whole sample and subsamples of interest. This is really neat because once they are created we can compute spatial autocorrelation coefficients directly using matrix commands or via regression with bootstrap of p-values :the moran scatterplots of Luc Anselin, which have the interest of providing real confidence intervals. My tests show small differences in results from GEODA and the GRETL scripts I use now. This is all good news and I will rest on your input to propose a few scripts and/or functions to compute tests for spatial autocorrelation I will submit to the community. I hope to write a short note and propose my scripts soon so that users can grasp the basics of those tests. Returning to the matter of neighbors, and programming, there are far smarter algorithms than the brute force hack I work on, but think it better to propose the simple scripts first before turning on the real smart ones which consist in exploring the neighborhood graph with special functions and pointers. More of this when the work will be more advanced. First i will propose the Moran spatial autocorrelation test as a function using two types of neighborhood structures: contiguity (common border) and nearest neighbors with choice in the number of neighbors on two kind of grids too: either square (checkboard) or hexagonal. Well, thanx very much Allin and Jack ! more about that soon ! cheers F. -- Franck Nadaud Economiste CIRED UMR 8568 CNRS - EHESS 45 bis avenue de la Belle Gabrielle 94736 Nogent-sur-Marne Cedex TEL 33-1-43-94-73-94 FAX: 33-1-43-94-73-70 MOB: 06-07-39-92-75 France