On Oct 21, 2010, at 9:47 AM, Federico Calboli wrote: > Mark, >> >> To the extent that it may be helpful here and I can do more if need be, I >> built 32 bit R 2.12.0 patched on Snow Leopard (10.6.4), using the R BLAS >> rather than Apple's veclib. This is on an early 2009 17" MBP with a 2.93 Ghz >> Core 2 Duo (MacBookPro5,2) and 4Gb of RAM. >> >> Based upon Doug's comment in this thread that the issue may be related to >> the use of Apple's veclib BLAS, as opposed to R's reference BLAS, I ran some >> tests. >> >> My config includes: >> >> --without-blas --without-lapack >> >> just to be sure that the above is the correct invocation, based upon what I >> found online. >> >> Using this build, with all CRAN packages freshly installed using this build, >> I ran the example used here with lme4 0.999375-35. I get: >> >> library(lme4) >> y <- (1:20)*pi; x <- (1:20)^2;group <- gl(2,10) >> M2. <- lmer (y ~ 1 + x + (1 + x | group)) >> M2 <- lmer (y ~ x + ( x | group)) >> >>> identical(fixef(M2), fixef(M2.)) >> [1] TRUE >> >> >> >> I then created a function so that I could use replicate() to run this test a >> "larger" number of times: >> >> testlme4 <- function() >> { >> y <- (1:20)*pi; x <- (1:20)^2;group <- gl(2,10) >> M2. <- lmer (y ~ 1 + x + (1 + x | group)) >> M2 <- lmer (y ~ x + ( x | group)) >> identical(fixef(M2), fixef(M2.)) >> } >> >> >> RES <- replicate(1000, testlme4()) >> >>> all(RES) >> [1] TRUE >> >>> table(RES) >> RES >> TRUE >> 1000 >> >> Does the example need to be run a "very large" number of times to be sure >> that it does not fail, or is the above a reasonable indication that the use >> of R's BLAS is a more appropriate default option for R on OSX? If I am not >> mistaken (and somebody correct me if wrong), R's BLAS is the default on >> Windows and Linux (from my recollections on Fedora). Why should OSX be >> different in that regard? > > Thanks for the very informative post. I added R-Mac in my reply to see if > someone can come up with a response to your query. It would also be > interesting to know if it were possible to switch the OSX R binary to use the > R BLAS library.
Yes, see R for Mac FAQ 12.5. Cheers, Simon >> >> Also, as an aside to Federico, I use 32 bit R on OSX largely because I have >> to interact with an Oracle server via RODBC. The only ODBC drivers available >> for Oracle on OSX are 32 bit and they are not compatible with 64 bit R. It >> would be rather cumbersome when running reports (via Sweave) to first >> extract the data in 32 bit R and then switch to 64 bit R to run the reports. >> I can run it all in a single step using 32 bit R. I also do not have a need >> for the larger memory address space afforded by 64 bit R. > > I'm very primitive in any integration between R and anything else, so much so > that I abandoned Emacs (well integrated with R) for Vim (not as well > integrated). On the other hand I do need the greater memory address space of > R64. I understand my needs and habits are not universally shared, but, if the > *only* reason for using R32 vs R64 is the 20% speed difference, I'd use R64 > for running lme4. > > Best, > > Federico > > > -- > Federico C. F. Calboli > Department of Epidemiology and Biostatistics > Imperial College, St. Mary's Campus > Norfolk Place, London W2 1PG > > Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 > > f.calboli [.a.t] imperial.ac.uk > f.calboli [.a.t] gmail.com > > _______________________________________________ > R-SIG-Mac mailing list > R-SIG-Mac@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/r-sig-mac > > _______________________________________________ R-SIG-Mac mailing list R-SIG-Mac@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-mac