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st: AW: More efficient way of programming


From   "Stephan Brunow" <Stephan.Brunow@mailbox.tu-dresden.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: AW: More efficient way of programming
Date   Tue, 6 Jun 2006 12:16:59 +0200

Hi,

there might be another way.
I do not know if it is a more efficient and less time consuming way, but it
might work:

reshape the data set to

id_i	id_j	dist
1	1	0
1	2	23
1	3	21
...
1	2500	530
and so on.

Get the shortest distance 
.by id_i, sort: egen mindist=min(dist) if dist>0

Now look for the station:
.gen helpvar=mindist-dist

which is zero for the closest station. Now you can make a small test first
and get the id (with a small way around):

.tab mindist (...this is the test)
.gen helpnear_id=id_j if helpvar==0
.replace helpnear_id=0 if helpnear_id==.
.by id_i, sort: egen near_id=max(helpnear_id)
.drop helpnear_id helpvar

Finally you might reshape again to get the result in a matrix.

However, I do not know if it is faster than 1.4 hours since reshape is a bit
more time consuming :-)

Stephan


---
Stephan Brunow
MSc. in Economics und Diplom-Verkehrswirtschaftler 
Professur für VWL, insb. Makroökonomik und
Raumwirtschaftslehre/Regionalwissenschaften
Institut für Wirtschaft und Verkehr
Fakultät für Verkehrswissenschaften „Friedrich List"
Technische Universität Dresden
D-01062 Dresden

 

http://tu-dresden.de/regionalscience 

Phone: ++49-(0)351-463-36806
Fax: ++49-(0)351-463-36819

-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Jitian Sheu
Gesendet: Dienstag, 6. Juni 2006 11:41
An: statalist@hsphsun2.harvard.edu
Betreff: st: More efficient way of programming

Dear listers:

I have a data set with the following structure:

id  d1   d2    d3.....      d2500   min_dis
1   0    23   21          530      21             
2   23   0
3
4
5
...
(up to 2500)

i.e. number of observation=2500, and each one represent to one station(id)
   dX= the distance to stationX, X=1...2500
   (since there are 2500 observation,==> I have 2500 distance variables)

   min_dis=minimum distance of the nearest station.


So, for each observation(station), I know its minimum distance to another
station.
Now, I want to know its nearest station id.
i.e. I want to have another variable (say called near_id). By this new
variable, I can then obtain the id number of each observation's nearest
station id.

For example (using the above data)
:	
id  d1   d2    d3.....      d2500   min_dis  ==> near_id
1   0    23   29          530      21     ==>     2
2   23   0    32          41       23     ==>     1
3   29   32   0            52       21    ==>     2
4
5
...

For this purpose, I use the following programming code.
Basically, I am doing this observation by observation:

gen near_id=.

forvalues	i=1(1)2500{

           forvalues	j=1(1)2500{
				replace near_id =`j'	if id==`i'&
d`j'==min_dis
						
				}
  		}

Therefore, there are totally 2500X2500 loops
If each loop takes 2 seconds==> totally, I need 5000 seconds to finish the
whole process, which is 1.4 hours.

Is there any efficient way to do that?

Many thanks.

JT


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