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<TITLE> Spatial econometrics functions library </TITLE>
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-------- spatial weights functions --------
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<A HREF = "disitance.m ">distance </A>: Computes the list of pairwise distances for a given set of locations
<A HREF = "find_neighbors.m ">find_neighbors </A>: finds observations containing m nearest neighbors, slow but low memory version
<A HREF = "find_nn.m ">find_nn </A>: finds observations containing m nearest neighbors, fast but high memory version
<A HREF = "find_nn2.m ">find_nn2 </A>: finds observations containing nn nearest neighbors, high-order search
<A HREF = "make_neighborsw.m">make_neighborsw </A>: finds the nth nearest neighbor and constructs
<A HREF = "make_nnw.m ">make_nnw </A>: finds the nth nearest neighbor and constructs
<A HREF = "make_nnwd.m ">make_nnwd </A>: An example of using make_nnw()
<A HREF = "normw.m ">normw </A>: normalize a spatial weight matrix
<A HREF = "normw_d.m ">normw_d </A>: An example of using normw() to produce a normalized 1st order contiguity matrix
<A HREF = "normxy.m ">normxy </A>: Perform isotropic normalization of x-y coordinates
<A HREF = "slag.m ">slag </A>: compute spatial lags
<A HREF = "slag_d.m ">slag_d </A>: An example of using slag()
<A HREF = "xy2cont.m ">xy2cont </A>: uses x,y coordinates to produce spatial contiguity weight matrices
<A HREF = "xy2cont_d.m ">xy2cont_d </A>: An example of using xy2cont()
<A HREF = "xy2cont_d2.m ">xy2cont_d2 </A>set for 1980 Presidential election results covering 3,107
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