Trouble getting development version of lme4
On 2/27/2013 7:59 PM, Ben Bolker wrote:
Ross Boylan <ross at ...> writes:
Running on Windows 7, R 2.15.2, I have been unable to get the development version of lme4 working. I'd appreciate any assistance. Following the instructions at http://lme4.r-forge.r-project.org/ 1. install.packages("lme4",repos="http://r-forge.r-project.org") Installing package(s) into
'c:/Users/rdboylan/Documents/R/R-2.15.2/site-library'
(as 'lib' is unspecified)
Warning message:
package 'lme4' is not available (for R version 2.15.2)
2.
install.packages("lme4",repos="http://lme4.r-forge.r-project.org/repos")
[snip]
Warning: dependencies 'minqa', 'Rcpp', 'RcppEigen' are not available
There is a binary version available (and will be installed) but the
source version is later:
binary source
lme4 0.999902344-0 0.999902345-0
Warning: dependencies 'minqa', 'Rcpp', 'RcppEigen' are not available
[snip]
Content type 'application/zip' length 2027695 bytes (1.9 Mb)
opened URL
downloaded 1.9 Mb
package 'lme4' successfully unpacked and MD5 sums checked
Warning: cannot remove prior installation of package 'lme4
## I had installed the one from CRAN, but detached and unloaded
it before attempting installation
# Do I need to manually delete the existing install?
You shouldn't need to. Normally this happens when the package is still loaded while you're trying to install, but ...
3. Then I tried to get the dependencies listed above from CRAN. This
mostly worked, but
package 'minga' is not available (for R version 2.15.2)
4. The end result:
> library(lme4)
Error in library(lme4) : there is no package called 'lme4'
Despite the message in 2, it appears lme4 was mostly removed, but
there is still a dll there. I thought detach unload was supposed
to take care of that.
My guess is exiting ESS and deleting the installed lme4 files will fix
some of the problems, but it looks as if one required package, minga, is
unavailable.
Well, the major problem with this is that the package is called 'minqa', not 'minga'.
Well, that's a good reason it didn't work! Unfortunately, I still have problems with it, perhaps because minqa and lme4 are coming from different sources built against different versions of R. I got minqa from 'http://r-forge.r-project.org/bin/windows/contrib/2.15/minqa_1.2.1.zip' and lme4 from 'http://lme4.r-forge.r-project.org/repos/bin/windows/contrib/2.15/lme4_0.999902344-0.zip' Neither is available on the other's repository. Then > library(lme4) Loading required package: lattice Loading required package: Matrix Error in inDL(x, as.logical(local), as.logical(now), ...) : unable to load shared object 'c:/Users/rdboylan/Documents/R/R-2.15.2/site-library/minqa/libs/i386/minqa.dll': LoadLibrary failure: Invalid access to memory location. Error: package/namespace load failed for 'lme4' BTW, ending the R session and exiting ess (but not emacs) did allow me to delete the residual old dll and install the new package.
I do apologize that things are a bit of a mess right now; we've
been having trouble with the R-forge build because of some version/
dependency problems with Rcpp.
A couple of general thoughts:
* development is now happening on github. If you want to install
the very latest version, and have the tools for compiling for source,
try
install.packages(c("Rcpp","RcppEigen","minqa","devtools"))
library("devtools")
install_github("lme4",user="lme4")
Do please let us/me know, if you try it, whether that works
and/or whether you encounter problems.
In general for installing from R-forge but wanting to be
able to get the dependencies from CRAN as well:
install.packages("lme4",repos=c("http://r-forge.r-project.org",
getOption("repos")))
In the very near future we hope to
(1) build some updated binaries and put them up at
http://lme4.r-forge.r-project.org/repos
That would be great.
(2) update the installation instructions (we may stop referring to the automatically built r-forge binaries, since these will start falling behind the version on github)
The binaries are a great convenience. The best news is that the CRAN version of lme4 seems able to do the poisson with my data as long as I don't specify nAGQ=. Since my immediate concern is using this inside an imputation procedure, great precision is probably not that important.