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... I could reproduce this behaviour under Linux and Solaris, the exact versions are given below. Z --- the problem exists on platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 1 minor 6.0 year 2002 month 10 day 01 language R and platform sparc-sun-solaris2.7 arch sparc os solaris2.7 system sparc, solaris2.7 status major 1 minor 6.0 year 2002 month 10 day 01 language R but not on platform i386-pc-linux-gnu arch i386 os linux-gnu system i386, linux-gnu status major 1 minor 5.1 year 2002 month 06 day 17 language R -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-devel-request@stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
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 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-devel-request@stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._