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st: More efficient way of programming


From   "Jitian Sheu" <jtsheu@mail.cgu.edu.tw>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: More efficient way of programming
Date   Tue, 6 Jun 2006 17:40:32 +0800

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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