growing process size in simulation

[Peter Dalgaard BSA]

Achim Zeileis <zeileis@ci.tuwien.ac.at> writes:

> I came across this in a simulation I ran under 1.6.0: If I do something
> like
> 
> R> x <- rnorm(10)
> R> rval <- NULL
> R> for(i in 1:100000) rval <- t.test(x)$p.value
> 
> then the process size remains at about 14M under 1.5.1, but it seems to
> be almost linearly growing up to more than 100M under 1.6.0.
> 
> I know that the above simulation is nonsense, but it was the simplest I
> could come up with to reproduce the behaviour. It doesn't depend on
> t.test, if I use wilcox.test(x)$p.value the same happens...

Argh. Confirmed. One interesting clue is that R itself doesn't seem to
know about this:

for(i in 1:50000) {
   rval <- t.test(x)$p.value 
   if (i %% 10000 == 0) print(gc())
}

         used (Mb) gc trigger (Mb)
Ncells 208343  5.6     407500 10.9
Vcells  64656  0.5     786432  6.0
         used (Mb) gc trigger (Mb)
Ncells 208343  5.6     407500 10.9
Vcells  64656  0.5     786432  6.0
         used (Mb) gc trigger (Mb)
Ncells 208343  5.6     407500 10.9
Vcells  64656  0.5     786432  6.0
         used (Mb) gc trigger (Mb)
Ncells 208343  5.6     407500 10.9
Vcells  64656  0.5     786432  6.0
         used (Mb) gc trigger (Mb)
Ncells 208343  5.6     407500 10.9
Vcells  64656  0.5     786432  6.0

..but the memory footprint is still growing.

-- 
   O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard@biostat.ku.dk)             FAX: (+45) 35327907
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