correlogram for categorical data

I have a 1000 x 1000 grid of categorical values (nine of these) and want
to compute and plot a correlogram.  Function cell2nb() will take a while
it appears but if that succeeds then can methods of sp.correlogram() be
used on categorical data?  What are "style" options in sp.correlogram()?

Sorry, could you say how a correlogram might be constructed for 
categorical values (eg. land cover)? Wouldn't join counts be a more 
natural choice? joincoint.multi() in spdep has a Jtot value of total 
different category joins, so using that with different lags of a cell2nb() 
neighbour list might work. However, the 1M cell grid is pretty large for 
cell2nb(), using dnearneigh() on cell centres may be faster and scale 
better, (and other possibilities should exist) and nblag() will be 
definitely sub-optimal in this setting. For join counts, the "B" weights 
style is the obvious one to chose. Note that joincoint.multi() is not 
coded in C.

This would need trying on a small subset and scaling up - I think that 
alternative routes to constructing the lagged neighbour lists would be 
preferable.

Roger

thanks,
Denis

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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: Roger.Bivand at nhh.no