[R-SIG-Mac] [R-sig-ME] lme4 missing from repositories?

[Marc Schwartz]

On Oct 21, 2010, at 8:47 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.
>> 
>> 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.



OK, so here is some more data.  I wondered if my build using R's BLAS may have possibly been a Type II error. So I re-built 32 bit R (same SVN checkout code) using:

  --with-blas='-framework vecLib' --with-lapack

I then completely removed my old R build (using R's BLAS) and the installed CRAN packages. I re-installed R using the above configuration and then cleanly re-installed the required CRAN packages.

Here are the results:

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] FALSE

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] FALSE

> table(RES)
RES
FALSE  TRUE 
  496   504 

So the test in question seems to fail with P(Failure) ~ 0.5 using Apple's veclib BLAS.

I should also note that all of my testing is from the CLI using the OSX terminal. I do not use R.app.

In response to Huang's reply, regarding his use of the shared lib approach, I wonder if there is some other interaction going on, either in the BLAS libs, or perhaps in the installed version of lme4, when one BLAS versus the other is in use at the time of lme4 installation, since it is installed from source on OSX. Note that I used a fully clean build of R and the required CRAN packages for each set of tests. 

If there is some other testing that I can do, let me know. But the above results with a clean build of R and lme4 each time, would seem to further reinforce a reconsideration of the use of Apple's veclib BLAS as the default for CRAN binary builds of R on OSX.

Regards,

Marc