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Today's Topics:
1. Re: Zero-inflated and proportional data (Highland Statistics Ltd)
2. Openblas and lme4 (Christian Brauner)
3. Re: Openblas and lme4 (Douglas Bates)
----------------------------------------------------------------------
Message: 1
Date: Sat, 15 Nov 2014 11:33:27 +0000
From: Highland Statistics Ltd <highstat at highstat.com>
To: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] Zero-inflated and proportional data
Message-ID: <54673A07.7020105 at highstat.com>
Content-Type: text/plain; charset=utf-8; format=flowed
Yes..it is possible. You can do this in JAGS (or OpenBUGS). You can find
JAGS code
for a beta GLM(M) in our 'Beginner's Guide to GLM and GLMM with R".
Extension
to a zero inflated beta binomial can be done via the zero trick in JAGS.
And you
will need to find the mean and variance of a zero inflated beta GLM.
Kind regards,
Alain Zuur
------------------------------
Message: 2
Date: Sat, 15 Nov 2014 15:09:35 +0100
From: Christian Brauner <christianvanbrauner at gmail.com>
To: r-sig-mixed-models at r-project.org
Subject: [R-sig-ME] Openblas and lme4
Message-ID: <20141115140934.GA746 at gmail.com>
Content-Type: text/plain; charset=utf-8
Hello,
For testing/research purposes I compiled R from source with blas as a
shared library. I then went on to compile openblas from source, tuned it
to Sandybridge and linked R against. The crucial step being:
cd /usr/local/lib/R/lib \
&& mv libRblas.so libRblas.so.old \
&& ln -s /usr/local/lib/libopenblas_sandybridgep-r0.2.12.so
libRblas.so
It worked perfectly and I see as output from /cat/pid/status:
Name: R
State: S (sleeping)
[?]
Threads: 4
[?]
Tests with the Matrix library confirm that threading works and the
increase in speed is significant for linear algebra operations such as
solve(), chol() etc.
I was wondering if lmer can make any use of this? I couldn't find a lot
on the internet. Just some posts from R-bloggers vaguely referencing
lme4 and some comments by Doug but I couldn't come to a conclusion
whether lme4 will see improvements in speed at least for larger models.
So far all my calls to lmer() on R with openblas run on a single core.
To pinpoint whether I did something wrong during compilation or if lme4
cannot reall profit from openblas I thought asking here might be a good
idea.
Best,
Christian
(For the sake of completeness: The exact compilation instructions I used
can also be found here
https://github.com/brauner/dockR/blob/master/r-patched-ivy-openblas/Dockerfile
.
Someone who runs an ivy- or sandybridge cpu and uses docker can also
pull a docker image with "docker pull brauner/rblas" and check for
himself if I did something wrong.)
------------------------------
Message: 3
Date: Sat, 15 Nov 2014 16:12:20 +0000
From: Douglas Bates <bates at stat.wisc.edu>
To: Christian Brauner <christianvanbrauner at gmail.com>,
r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] Openblas and lme4
Message-ID:
<
CAO7JsnQ_PaT7HZbUr4A_ASuk2xWA5sTUeoqSw0V9+2FPt-r_dA at mail.gmail.com>
Content-Type: text/plain; charset="UTF-8"
The bulk of the linear algebra calculations in lme4 are done using the
Eigen C++ library which does not rely on the BLAS. Thus a multi-threaded
BLAS will not affect lme4 speed to any great extent. I believe that Eigen
has its own multi-thread capabilities but it has been a while since I
checked.
On Sat Nov 15 2014 at 8:05:00 AM Christian Brauner <
christianvanbrauner at gmail.com> wrote:
Hello,
For testing/research purposes I compiled R from source with blas as a
shared library. I then went on to compile openblas from source, tuned it
to Sandybridge and linked R against. The crucial step being:
cd /usr/local/lib/R/lib \
&& mv libRblas.so libRblas.so.old \
&& ln -s /usr/local/lib/libopenblas_sandybridgep-r0.2.12.so
libRblas.so
It worked perfectly and I see as output from /cat/pid/status:
Name: R
State: S (sleeping)
[?]
Threads: 4
[?]
Tests with the Matrix library confirm that threading works and the
increase in speed is significant for linear algebra operations such as
solve(), chol() etc.
I was wondering if lmer can make any use of this? I couldn't find a lot
on the internet. Just some posts from R-bloggers vaguely referencing
lme4 and some comments by Doug but I couldn't come to a conclusion
whether lme4 will see improvements in speed at least for larger models.
So far all my calls to lmer() on R with openblas run on a single core.
To pinpoint whether I did something wrong during compilation or if lme4
cannot reall profit from openblas I thought asking here might be a good
idea.
Best,
Christian
(For the sake of completeness: The exact compilation instructions I used
can also be found here
https://github.com/brauner/dockR/blob/master/r-patched-
ivy-openblas/Dockerfile.
Someone who runs an ivy- or sandybridge cpu and uses docker can also
pull a docker image with "docker pull brauner/rblas" and check for
himself if I did something wrong.)
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