Thank you. I tried Rprof and looks like aggregate function I am using is one
of the functions that takes most of the time. What is the difference between
self time and total time?
$by.total
total.time total.pct self.time self.pct
f 925.92 99.98 5.16 0.56
<Anonymous> 925.92 99.98 0.06 0.01
nlm 925.92 99.98 0.00 0.00
aggregate 885.66 95.64 0.28 0.03
aggregate.default 885.38 95.61 0.02 0.00
aggregate.data.frame 885.34 95.60 12.54 1.35
lapply 817.06 88.23 183.76 19.84
FUN 814.48 87.95 53.50 5.78
split 425.06 45.90 4.50 0.49
split.default 420.56 45.41 14.16 1.53
factor 408.84 44.15 347.12 37.48
unique 235.32 25.41 19.38 2.09
sapply 202.60 21.88 1.70 0.18
unlist 181.40 19.59 132.28 14.28
simplify2array 148.70 16.06 1.10 0.12
[[<- 41.24 4.45 1.62 0.17
[[<-.data.frame 39.62 4.28 31.42 3.39
^ 26.18 2.83 26.18 2.83
jholtman wrote
> use Rprof to profile your code to determine where time is being spent.
> This might tell you where to concentrate your effort.
>
> Sent from my iPad
>
> On Oct 25, 2012, at 23:23, stats12 <
> skarmv@
> > wrote:
>
>> Dear R users,
>>
>> I need to run 1000 simulations to find maximum likelihood estimates. I
>> print my output as a vector. However, it is taking too long. I am running
>> 50
>> simulations at a time and it is taking me 30 minutes. Once I tried to run
>> 200 simulations at once, after 2 hours I stopped it and saw that only
>> about
>> 40 of them are simulated in those 2 hours. Is there any way to make my
>> simulations faster? (I can post my code if needed, I'm just looking for
>> general ideas here). Thank you in advance.
>>
>>
>>
>> --
>> View this message in context:
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>> Sent from the R help mailing list archive at Nabble.com.
>>
>> ______________________________________________
>>
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>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
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> PLEASE do read the posting guide
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