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Re: st: Adjacency matrix in Stata


From   jean-luc morin-chesnel <[email protected]>
To   [email protected]
Subject   Re: st: Adjacency matrix in Stata
Date   Sun, 30 Mar 2014 21:44:00 +0200

what i want to say is that (assume I have "only" 500 individuals)
what would be the algorithm to obtain the adjacency matrix above in Stata?

thanks again for your time

On 30 March 2014 19:46, jean-luc morin-chesnel
<[email protected]> wrote:
> Thank you very much, Stas!
>
> Maybe I can reduce my dataset to, lets say 5k individuals?
> What would you do? Do you have other alternatives in mind?
>
> Thanks!
>
> JL
>
> On 30 March 2014 19:34, Stas Kolenikov <[email protected]> wrote:
>> It would be cumbersome whichever way you want to look at it. And at
>> any rate Stata won't be able to store a 100K x 100K matrix... only 11K
>> x 11K matrices (see -help limits- and -set matsize-).
>>
>> -- Stas Kolenikov, PhD, PStat (ASA, SSC)
>> -- Principal Survey Scientist, Abt SRBI
>> -- Opinions stated in this email are mine only, and do not reflect the
>> position of my employer
>> -- http://stas.kolenikov.name
>>
>>
>>
>> On Sun, Mar 30, 2014 at 11:55 AM, jean-luc morin-chesnel
>> <[email protected]> wrote:
>>> Dear all,
>>>
>>> I have a panel dataset at the individual - day - product level
>>> (unbalanced) and I would like to obtain a adjacency matrix in Stata,
>>> but I do not know how to proceed.
>>>
>>> That is, I assume that 2 individuals are connected in the network if
>>> they buy the same product the same day more than N times in my dataset
>>> (lets say N=10).
>>>
>>> So I would like to obtain a matrix of adjacency in Stata: a MxM matrix
>>> (M in the number of investors) where the coefficient mij=1 iff
>>> investor i and investor j are connected in the network.
>>>
>>> I do not know how to proceed because I think that I should use loops,
>>> but it seems to me that it is not very efficient to do so in Stata
>>> (the dataset is large: 100k individuals). Any suggestion is very
>>> welcomed.
>>>
>>> Many thanks,
>>> Regards,
>>>
>>> JL
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