[R-sig-Geo] Fitting SAR models in spdep (was: spatial 2SLS)

Roger Bivand Roger.Bivand at nhh.no
Mon Dec 13 19:21:00 CET 2004 

On Mon, 13 Dec 2004, Danlin Yu wrote:

> Dear Professor Roger Bivand:
> 
>     Yes, I was talking about the two SAR fitting functions. I just did a
> very quick run on a dataset with 3437 observations (those are point data,
> and I generate the listw object using dnearneigh() - not sure whether the
> result is symmetric or asymmetric). 

How many links are there in the neighbour list? Distance neighbours are 
symmetric, but if points are densely placed, there may be parts of your 
study area with many neighbours. Use print.nb() to find out how many.

> However, I tried both "sparse" and
> "SparseM" method on errorsarlm(), both failed to go through, the errors
> given as follow:
> 
>     For "sparse" method:
>     "Error in spwdet(sparseweights, rho = rho, debug = debug) : 
>         Suspicious allocation of memory in sparse functions
>          ...bailing out! Save workspace and quit R!"

Yes, this is the memory bug. It does happen on most/all GCC compiled 
versions, but I've seen BSD versions that work - it depends on the memory 
allocation code, but it has not been possible to solve. I am planning to 
drop "sparse" before long, unless the memory bug is resolved.

> 
>     For "SparseM" method:
>     "Error in .local(x, ...) : Increase tmpmax

This is the problem: tmpmax is defined in chol() for "matrix.csr" objects 
as only 10 times the number of rows. I think you have more neighbour links 
than 10*n, and that means I need to find a way of passing a better value 
through. Please let me know, this looks do-able.

Roger

>      Error in det(chol(x)) : Unable to find the argument "x" in selecting
>      a method for function "det" "
> 
>     By the way, I am still using R 2.0.0 and when I loaded the libraries,
> I got warnings. I will keep trying and keep you posted as I progress.
> Thanks.
> 
> 
> On Mon, 13 Dec 2004, Roger Bivand wrote:
> 
> > On Mon, 13 Dec 2004, Danlin Yu wrote:
> > 
> > > Dear Mihai Nica:
> > > 
> > >     I think it is a memory issue, too. I ran into the same problem when
> > > using around 3000 observations. Although I used memory.size() to increase
> > > the memroy allocation size, spdep took too long to run.
> > > 
> > 
> > I think you mean the two SAR fitting functions, lagsarlm() and 
> > errorsarlm()? The default method is "eigen", which does need plenty of 
> > memory with large n (because it both solves the eigenproblem for an nxn 
> > matrix, and later inverts an nxn matrix). There has always been a "sparse" 
> > method using code from Netlib called sparse from UCB, which works on some 
> > platforms, but not others, and has an unresolved memory bug. 
> > 
> > I'm pleased to report that Roger Koenker has been kind enough to add a
> > det() for symmetric (and similar to symmetric) sparse matrices to the
> > SparseM package. From spdep_0.3-5, spdep depends on SparseM, and
> > errorsarlm() is now pretty dependable for large n and fast. lagsarlm() is
> > dependable, but its fitting speed is slowed by fitting models for LR tests
> > dropping each of the X variables in turn, as well as the specified model,
> > so that it fits k models, not just 1. The function calls for the lag
> > models are cheaper than the error models, though.
> > 
> > The restriction to symmetric (and similar to symmetric) sparse matrices is
> > important to bear in mind. With symmetric neighbour lists (contiguity,
> > graphe-based and distance bands), and even symmetric inverse distances,
> > and all weighting styles this is OK (because "W" and "S" style are similar
> > to symmetric, and the others are symmetric), but absolutely not for
> > k-nearest-neighbours or for asymmetric general weights (say migration
> > tables).
> > 
> > I would be very interested in hearing whether this approach is helpful, 
> > and how this scales.
> > 
> > Roger
> > 
> > >     The problem, I think, might be due to the fact that spdep's spatial
> > > autoregressive models use the exact method (correct me if I am wrong),
> > > while GeoDa uses an approximatioin method (see the paper "Fast maximum
> > > likelihood estimation of very large spatial autoregressive models: a
> > > characteristic polynomial approach", in Computational Statistics & Data
> > > Analysis 35 (2001) 301-319). If the method could be incorporated in R, it
> > > will be great.
> > > 
> > >     Danlin
> > > 
> > > On Mon, 13 Dec 2004, Mihai Nica wrote:
> > > 
> > > > Greetings:
> > > > 
> > > > I would like to take advantage of this thread and ask if there is a way to
> > > > "enhance" the code in spdep. I have a dataset with 3030 observations and two
> > > > independent variables. On the same old computer it runs great in GeoDa, but
> > > > fails in R. I assume it is a memory issue, but having two different ways to
> > > > check my results would be great.
> > > > 
> > > > Thanks,
> > > > 
> > > > Mihai Nica
> > > > Jackson State University
> > > > 155 B Parkhurst Dr.
> > > > Jackson, MS 39202
> > > > 601 914 0361
> > > > 
> > > > ----- Original Message ----- 
> > > > From: "Luc Anselin" <anselin at uiuc.edu>
> > > > To: "Darla Munroe" <munroe.9 at osu.edu>
> > > > Cc: <r-sig-geo at stat.math.ethz.ch>
> > > > Sent: Monday, December 13, 2004 8:36 AM
> > > > Subject: Re: [R-sig-Geo] spatial 2SLS
> > > > 
> > > > 
> > > > > I have some functions that implement this. We used them in last summer's
> > > > > ICPSR spatial regression course. They are not (yet) very user friendly
> > > > > and
> > > > > not up to official R standards yet, but they definitely work.
> > > > > The functions include:
> > > > > - standard 2SLS (or IV estimation)
> > > > > - spatial 2SLS (using WX as instruments for Wy)
> > > > > - heteroskedastic robust spatial 2SLS (White adjusted variances)
> > > > > Anyone who wants them and doesn't need a lot of hand holding can e-mail
> > > > > me directly.
> > > > > L.
> > > > >
> > > > >
> > > > > On Dec 13, 2004, at 8:21 AM, Darla Munroe wrote:
> > > > >
> > > > > > Is the spatial 2SLS developed by Kelejian available in spdep?  If not,
> > > > > > is it
> > > > > > available anywhere else at this time?  (besides in SpaceStat).
> > > > > >
> > > > > >
> > > > > >
> > > > > > Thanks,
> > > > > >
> > > > > > Darla Munroe
> > > > > >
> > > > > >
> > > > > > [[alternative HTML version deleted]]
> > > > > >
> > > > > > _______________________________________________
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> > > > > >
> > > > >
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> > > > 
> > > 
> > >     Sincerely,
> > >     Danlin Yu
> > > 
> > > ----------------------------------
> > > Lecturer, Ph.D. Candidate
> > > Department of Geography
> > > University of Wisconsin, Milwaukee
> > > Tel: (414)229-3943
> > > Fax: (414)229-3981
> > > Email: danlinyu at uwm.edu
> > > 
> > > _______________________________________________
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> > > 
> > 
> > -- 
> > Roger Bivand
> > Economic Geography Section, Department of Economics, Norwegian School of
> > Economics and Business Administration, Breiviksveien 40, N-5045 Bergen,
> > Norway. voice: +47 55 95 93 55; fax +47 55 95 93 93
> > e-mail: Roger.Bivand at nhh.no
> > 
> > 
> 
>     Sincerely,
>     Danlin Yu
> 
> ----------------------------------
> Lecturer, Ph.D. Candidate
> Department of Geography
> University of Wisconsin, Milwaukee
> Tel: (414)229-3943
> Fax: (414)229-3981
> Email: danlinyu at uwm.edu
> ----------------------------------
> 
> 

-- 
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Breiviksveien 40, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 93 93
e-mail: Roger.Bivand at nhh.no

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