On Mon, 10 Sep 2007, E. Anthon Eff wrote: > Please forgive what may be a naive question. I'm working on a model that > requires two different weight matrices, as in the "biparametric" model > introduced by Brandsma and Ketellapper in 1979. I haven't had any luck > finding a way to do this in R. Any suggestions?
The spatial error model fitting functions spautolm() and errorsarlm(), and the spatial lag model fitting function lagsarlm() only fit a single set of spatial weights, by optimising in one dimension. It would be possible to generalise them to optimise in more than one dimension, but is it justified? Is there a very clear behavioural model that requires the fitting of more than one spatial regression coefficient that is driving thw question? Is it going to be practical to fit more than one coefficient on a probably rather flat surface? The slm() function in S-Plus SpatialStats module can do this for the error model if need be, but there is a case to be made for why it is necessary, unless there is a clear behavioural model. Roger > Thanks! > Anthon > > Brandsma A S, Ketellapper R H, 1979, "A biparametric approach to spatial > autocorrelation" /Environment and Planning A/ *11*(1) 51 ? 58 > > -- Roger Bivand Economic Geography Section, Department of Economics, Norwegian School of Economics and Business Administration, Helleveien 30, N-5045 Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43 e-mail: [EMAIL PROTECTED] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo