And, please report your OS and version of R (64-bit presumably?).
On Fri, Nov 19, 2010 at 10:39 AM, Michael Sumner <mdsum...@gmail.com> wrote:
> In general you need at least twice the required memory, and it has to
> be contiguous. Try with a fresh instance of R and try to create a
> single vector of that size, that might show that you *could* do it.
>
> Otherwise, check out the ff package, and see other options in the High
> Performance Computing Task View on CRAN.
>
> There may be other techniques you can use to solve the problem, but
> those two things are my direct answers to your questions.
>
> Cheers, Mike.
>
> On Fri, Nov 19, 2010 at 10:28 AM, Aleksandr Andreev
> <aleksandr.andr...@gmail.com> wrote:
>> Hello list,
>>
>> I have 120,000 geocoded observations, for which I'm trying to create a
>> distance-based spatial weighting matrix so that I can perform a Moran
>> test.
>>
>> Each observation has Lat and Lon.
>>
>> Unfortunately, when I run
>> dists <- as.matrix(dist(cbind(Lon, Lat)))
>> I get the message:
>> Error in vector("double", length) : vector size specified is too large
>>
>> Now I realize that 120,000^2 / 2 is on the order of 6 GB. However, I
>> seem to be running into software limitations on the vector size before
>> I hit RAM limitations. Also, in principle, it should be possible
>> (though slow) to use hard disk space to store this matrix. Does anyone
>> have any ideas on how to do this in R?
>>
>> Thanks,
>>
>> ------------------------
>> Aleksandr Andreev
>> Graduate Student - Department of Economics
>> University of North Carolina at Chapel Hill
>>
>> _______________________________________________
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>> R-sig-Geo@stat.math.ethz.ch
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>>
>
>
>
> --
> Michael Sumner
> Institute for Marine and Antarctic Studies, University of Tasmania
> Hobart, Australia
> e-mail: mdsum...@gmail.com
>
--
Michael Sumner
Institute for Marine and Antarctic Studies, University of Tasmania
Hobart, Australia
e-mail: mdsum...@gmail.com
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