[R] re-sampling of large sacle data

jd6688 jdsignature at gmail.com
Tue Jul 27 23:43:48 CEST 2010


myDF:

d1		d2		d3                      d4                        d5
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.000925938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.000925938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938
-0.166910351	0.022304377	-0.00825924	0.008330689	-0.168225938


per the dataframe above,
step 1: do the following

        
doit=function(x)c(sum_positive=sum(x[-1][x[-1]>0]),sum_negative=sum(x[-1][x[-1]<0]))

          pos_neg_pool<-t(apply(myDF,1,doit))
          if not first run then append the data to the pos_neg_pool
step2:  reshuffle the data by columns then do step1, this step need to run
10000 times;

output will be 23*10000=230,000 rows.

Can anyone point out how to automate this 10000 runs in R?

Thanks,


          



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