Some time ago, you used to be able to install the rcom package in R to use COM scripting (eg, access to external programs.) Unfortunately, it seems to be discontinued:
Package ‘rcom’ was removed from the CRAN repository.
Formerly available versions can be obtained from the archive.
This depends on statconnDCOM, which nowadays restricts use, contrary
to the CRAN policy for a package with a FOSS licence. See
http://rcom.univie.ac.at/ and http://www.statconn.com/.
Following the archive and statconn links and installing one of the older versions in R version 3 gives the error:
“Error: package ‘rcom’ was built before R 3.0.0: please re-install
it”.
I am not very familiar with R, but there seems no way around this message - after all, it occurs when installing, so re-installing doesn't seem to be the answer. It appears as though rcom is simply not available for recent (3.0+) versions of R. I have also scanned the package list, although searching for "COM" there returns over a hundred results and it is possible I missed the right one when clicking through them.
How can I use the rcom package, or use COM from within R some other way?
(Note: I am asking this question on behalf of a colleague. I have no experience with R myself at all. Both of us, when searching for answers, could not find anything. I am sure that others are also using COM in the latest version of R, though!)
I looked at the rcom source code a few months ago. It seems I can get it to build and install OK on R3.0.1. Below is the procedure if it helps.
Get a checkout of the latest source code of rcom. I have rcom_2.2-5.tar.gz locally. I can google something at the following address, but I have no idea of the provenance, so up to you to check it is legit. http://cran.open-source-solution.org/web/packages/rcom/index.html
in R do install.packages('rscproxy')
install Rtools as per the instructions on the R web site (http://cran.r-project.org/bin/windows/Rtools),
open a Windows command prompt i.e. run "CMD"
go to the folder containing the 'rcom' folder, and at the command prompt:
set R="c:\Program Files\R\R-3.0.1\bin\i386\R.exe"
%R% CMD check --no-manual rcom
check it passes without too many complaints. Your call as to the --no-manual option (if you have MiKTeX installed you may remove it)
%R% CMD INSTALL rcom
should result in
installing to c:/Rlib/rcom/libs/i386
** R
** inst
** preparing package for lazy loading
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded
rcom requires a current version of statconnDCOM installed.
To install statconnDCOM type
installstatconnDCOM()
This will download and install the current version of statconnDCOM
You will need a working Internet connection
because installation needs to download a file.
* DONE (rcom)
in R:
library(rcom)
installstatconnDCOM()
I tried a comRegisterRegistry() ; comRegisterServer()
; x<-comGetObject("Excel.Application") but I get a NULL for x. I am not a user of rcom so while it all seems to compile fine; it may just not work anymore.
If you happen to need to access .NET code, a viable option (and yes I have a vested interest in mentioning it) may be the rClr package.
Hope this helps; I'd be interested to hear how you go.
This really should be a comment, but I don't have enough rep points yet to leave one.
I found that the above steps did not work for me, but the answer posted by Lisa Ann on this question, RExcel in R 3.0.x, did solve my problem installing rcom. Since you need rcom to run RExcel, the initial steps to install RExcel cover installing rcom on newer versions of R (such as 3.0.2).
Specifically, following the advice on statconn's wiki, http://homepage.univie.ac.at/erich.neuwirth/php/rcomwiki/doku.php?id=wiki:how_to_install
You also need to follow these instructions if you upgrade R, i.e. you install a new >release of R after you have installed RExcel.
Download the statconn DCOM server and execute the program you downloaded
Start R as administrator (on Windows 7 you need to right-click the R icon and click the >corresponding item)
In R, run the following commands (you must start R as administrator to do this)
install.packages(c("rscproxy","rcom"),repos="http://rcom.univie.ac.at/download",lib=.Library)
library(rcom)
comRegisterRegistry()
Now you have rcom installed, [instructions for installing RExcel follow...]
New versions of rcom and rscproxy (also for current versions of R) are available from a different repository. Just use http://rcom.univie.ac.at/download as the R repository to install from and you can download and install binary versions of statconn packages from there.
Hope this helps!
Related
This, question, is, asked, over, and, over, and, over,
on the R-sig-finance mailing list, but I do not think it has been asked on stackoverflow.
It goes like this:
Where can I obtain the latest version of package XYZ that is hosted on R-forge? I tried to install it with install.packages, but this is what happened:
> install.packages("XYZ",repos="http://r-forge.r-project.org")
Warning message: package ‘XYZ’ is not available (for R version 2.15.0)
Looking on the R-forge website for XYZ, I see that the package failed to build.
Therefore, there is no link to download the source. Is there any other way
to get the source code? Once I get the source code, how can I turn that into a
package that I can load with library("XYZ")?
R-Forge may fail to build a package for a few different reasons. It could be that
the documentation has not been updated to reflect recent changes in the code. Or,
it could be that some of the dependencies were not available at build time.
You can checkout the source code using svn. First, search for the project on the
R-Forge website and go to the project home page -- for example http://r-forge.r-project.org/projects/returnanalytics/
Click the SCM link to get to a page like this http://r-forge.r-project.org/scm/?group_id=579
This page will tell you the command to use to checkout the project. In this case you get
This project's SVN repository can be checked out through anonymous access with the following command(s).
svn checkout svn://svn.r-forge.r-project.org/svnroot/returnanalytics/
If you are on Windows, you probably want to download and install TortoiseSVN
Once you have installed TortoiseSVN, you can right click in a Windows Explorer window and select
"SVN checkout". In the "URL of repository:" field, enter everything except the
"svn checkout " part of the command that you found on R-Forge. In this case, you'd
enter "svn://svn.r-forge.r-project.org/svnroot/returnanalytics/".
When you click OK, the project will be downloaded into the current directory.
If you are on a UNIX-alike system (or if you installed the command line client tools
when you installed TortoiseSVN for Windows, which is not the default), you can
type the command that R-forge gave you in your terminal (System terminal, not the R terminal)
svn checkout svn://svn.r-forge.r-project.org/svnroot/returnanalytics/
That will create a new directory under the current working directory that
contains all of the files in the package. In the top level of that directory
will be a subdirectory called "pkg". This particular project (returnanalytics)
contains more than one package.
ls returnanalytics/pkg
#FactorAnalytics MPO PApages PerformanceAnalytics PortfolioAnalytics
But some R-forge projects only have a single package. e.g.
svn checkout svn://svn.r-forge.r-project.org/svnroot/random/
#Checked out revision 14.
ls random/pkg
#DESCRIPTION inst man NAMESPACE R
Now that you have a local copy all of the code, if you would like to be able to
install the package, you have to build it first.
A WORD OF CAUTION: Since R-Forge failed to build the package, there is a good chance
that there are problems with the package. Therefore, if you just build it, you may find
that some things do not work as expected. In particular, it is likely that there
is missing or incomplete documentation.
If you are on a UNIX-alike system, the package can be built and installed relatively easily. For a multi-package project like returnanalytics, if you want to install, e.g. the
PortfolioAnalytics package, you can do it like this
R --vanilla CMD INSTALL --build returnanalytics/pkg/PortfolioAnalytics
"PortfolioAnalytics" is the name of the directory that contains the package that
you want to build/install. For a single-package project, you can build and install like
this
R --vanilla CMD INSTALL --build random/pkg
If you would like to build/install a package on Windows, see this question and follow the two links that #JoshuaUlrich provided
More information can be found in R Installation and Administration, the R-Forge User Manual, and the SVN manual.
If (and only if) you have the appropriate toolchain for your OS, then this may succeed:
# First download source file to your working directory
# As an example use browser to download pkg:partykit from:
# http://download.r-forge.r-project.org/src/contrib/partykit_1.1-2.tar.gz
# Move to working directory
# Or in the case of returnanalytics (which is a bundle of packages):
# http://r-forge.r-project.org/R/?group_id=579 and download the tar.gz (source)
# Then in R:
install.packages( "partykit_1.1-2.tar.gz", repo=NULL, type="source")
# for the first of the ReturnAnalytics packages:
install.packages( "Dowd_0.11.tar.gz", repo=NULL, type="source")
These direction should be "cross-platform". I'm not sure the directions in the accepted answer are applicable to Macs (OSX). (I later confirmed that they do "work" on a Mac but found the process more involved that what I suggested above. They do result in a directory that do contain the packages in a form that should succeed with R --vanilla CMD INSTALL --build pathToEachPackageSeparately)
It is also possible that the current version of the package you are trying to install requires a newer version of R, for example, you may see error like:
"ERROR: this R is version 2.15.0, package 'PerformanceAnalytics' requires R >= 3.0.0"
then you can try to update your R
or, if you are facing the same situation with me, which is trying to use pqR (currently using R version 2.15), you can find the out-of-date achieved package here:
http://cran.at.r-project.org/src/contrib/Archive/PerformanceAnalytics/
You can get here from R-Forge packages page -> "Stable Release: Get PerformanceAnalytics 1.4.3541 from CRAN" -> Old sources: PerformanceAnalytics archive
for example, you will find package PerformanceAnalytics version 1.1.0 just requires R >= 2.14
Good luck
Alternatively, you can install the particular package from GitHub, if it has a repo at GitHub.
I ran install.packages('ggfortify'), and got
Warning message: “package ‘ggfortify’ is not available (for R version
3.3.2)”
ggfortify was the GitHub repo for the same package.
The devtools library allows you to install a package from GitHub directly with install_github('username/repo').
library(devtools)
install_github('sinhrks/ggfortify')
My Fedora system (Fedora 20, all up to date) has just had R updated to version 3.1.0. Since then, I've had issues installing multiple packages. glmnet failed previously, and now I'm having trouble with treemap. More specifically, I get an error during treemap installation that httpuv has zero exit status.
I never had issues with the previous version of R. Any reason this version should have such problems??
There could be many causes to do with your OS, version, permissions, other installed packages/software, etc, etc. Without seeing the full error message it's hard to know.
One possibility specific to httpuv is root privileges. I've noticed a few threads on various forums when searching for installation errors with this package and Linux, many of them mentioning root v. non-root issues. In another case, libuv needed to be upgraded.
I encounter package installation problems daily and I have some more general work-arounds as well. Hopefully one of these will solve your problem.
Install the package from source
download.file(url="http://cran.r-project.org/src/contrib/httpuv_1.3.0.tar.gz", destfile = "httpuv.tar.gz")
install.packages("httpuv.tar.gz", type = "source", repos = NULL)
Install using devtools via GitHub if the package supports it
Install RTools and re-try your package installation
Install an older version of the package
If those above do not work, then I dig deeper by referring to advice given to me by a VP of IT in my company. These comments were made in reference to frequent package installation problems I encountered when switching from Windows to Solaris:
There are two types of install/make problems. Missing .h files
and/or missing .so/.a libs. The reason for these are multiple:
1.- the package that delivers these is not installed. This means that those files cannot be found anywhere in the /usr tree. Solution is
install right package, make sure the files are there
2.- the includes are not found by the install configurator. This means some environment variable or install option is not properly set (this
is our case for RODBC). Figuring out which variable to set is
challenging without looking at the package documentation [fortunately, documentation is not hard to find!]
3.- the libs are not in the LD_LIBRARY_PATH, easy to fix.
4.- There is a deeper compile/link error, meaning the package is not compatible with the rest of the sw, or has not been properly ported.
Problem:
C:\>Rcmd.exe INSTALL --build --library=C:/Users/local_aphalo/Documents/R/win-library/3.0 photobiology
C:\>Rcmd.exe INSTALL --build --library=C:/Users/local_aphalo/Documents/R/win-library/3.0 photobiology_0.2.6.tar.gz
The first command (as used by RStudio) builds a ZIP file that is missing the vignettes.
The second command builds a ZIP that includes the vignettes.
Using R CMD instead of Rcmd.exe makes no difference. The .tar.gz was built immediately before attempting to build the .zip file, from exactly the same source files, from within RStudio (which uses Rcmd.exe build photobiology).
The vignettes are coded in .Snw files using knitr, documentation and NAMESPACE use ROxygen2. The problem happens on all of the packages that I have tried to build, but they are very similarly coded. Only one of them uses Rcpp.
When installing the package for use from within RStudio, installing from .tar.gz installs vignettes just fine. If installing from .zip, whether vignettes get installed or not, depends on whether the .zip files contains them or not (which depends on which of the two commands at the top of this message was used to build the .zip file).
I am using R 3.0.1, and also tried a couple of R 3.0.1 patched builds a few days back. I am mostly using Windows 7 (both 32 bit, and 64 bit), I tried once under Ubuntu 64bit, and the problem is reproducible. I first noticed the problem when using RStudio (0.97 and 0.98) and posted a message in the RStudio forum, but have received no answer in a couple of weeks. I have found at least another relatively old post about this problem in the RStudio website forum, but it has not been answered. Today, I investigated a bit further, and the problem is clearly not related to RStudio, as I can reproduce it through the command line.
The question is: Is this behavior a feature? a bug? or I am missing just an option in the command used?
Of course, I can easily work around the problem at the command line by using the .tar.gz file to build the .zip file, but as I think the preferred way of building a package is by just supplying the package name as argument.
Thanks for any insights on the origin of this problem.
I think this is a feature:
if you're installing from source, vignettes are always built
if you're installing from a binary, they're not built, and will only be available if they were built when the binary was made
This approach means that you can distribute vignettes in binary packages to people who might not be able to build them from source.
I was trying to run code that required the R packages ‘pkgDepTools’ and ‘Rgraphviz’. I received error messages saying that neither package is available for R version 2.15.0.
A Google search turned up the following webpage RPM Pbone that seems to have the packages:
http://rpm.pbone.net/index.php3/stat/4/idpl/17802118/dir/mandrake_other/com/R-pkgDepTools-1.20.0-1-mdv2012.0.i586.rpm.html
and
http://rpm.pbone.net/index.php3/stat/4/idpl/17802080/dir/mandrake_other/com/R-Rgraphviz-1.32.0-2-mdv2012.0.i586.rpm.html
However, the files have an *.rpm extension rather than the *.tar.gz or *.zip extensions I am used to.
I am using Windows 7 and R version 2.15.0. Can I install an R package from an *.rpm file?
From Wikipedia *.rpm seems like maybe it is more for Linux:
http://en.wikipedia.org/wiki/RPM_Package_Manager
Regarding other possible solutions, I have found several earlier posts here with similar questions about installing R packages that are not available for the most recent version of R:
Bivariate Poisson Regression in R?
Package ‘GeneR’ is not available
R Venn Diagram package Venerable unavailable - alternative package?
I have installed the latest version of Rtools and the package 'devtools'. Although I know nothing about them.
There is an archived version of 'Rgraphviz' here:
http://cran.r-project.org/src/contrib/Archive/Rgraphviz/
but I cannot locate an archived version of 'pkgDepTools'.
If I can install the packages on a Windows machine using the above *.rpm files could someone please provide instructions?
If I must use Rtools to build them I might ask more questions because the instructions at the link below are challenging for me:
http://cran.r-project.org/doc/manuals/R-admin.html#Building-from-source
To be completely transparent I am hoping someone might build them for me, if that is possible. Although I recognize the experience and knowledge gained from doing it myself would probably pay off in the long run.
Thank you for any advice.
pkgDepTools and Rgraphviz are BioConductor R packages not ones hosted on CRAN. Unless you configure your R to download packages from those repos, R will report that they are not available; it can only install from repos it has been configured to install from.
To install those BioConductor packages a lite installation method is provided:
source("http://bioconductor.org/biocLite.R")
biocLite(c("pkgDepTools", "Rgraphviz"))
Further details are provided on the Install page of the BioConductor website
In general you can't use rpm packages on Windows; rpm's are the equivalent of a binary package for Linux. Any C/C++/Fortran/etc code will have been compiled for Linux not Windows. If a package really isn't available for your version of R then check if there is a reason stated on CRAN (usually Windows binaries take a few days longer to produce or there may be requirements for software not available on the CRAN Windows build machines). You can try the WinBuilder service run by Uwe Ligges to build Windows Binaries of packages for you, but if the package was on CRAN and now isn't that suggests it no longer works with current R and can not be built.
In general try a wider search for packages; the first hit in my Google search results under the search string "pkgDepTools" is the Bioconductor page for the package which includes a link to the Windows binary and instructions on how to install the package from within R.
I think this merits an answer rather than a comment.
A gentleman at Bioconductor helped me get Rgraphviz installed. The primary problem was that the version of Rgraphviz I had downloaded only seems to work with the 32-bit version of R and I was running a 64-bit version of R. I was able to install Rgraphviz in the 32-bit version of R.
I had also made an error or two in the PATH statement during some of my attempts to install Rgraphviz. However, the post above in my second comment provides the instructions for installation.
You just, it seems, cannot install the normal download version of Rgraphviz in the 64-bit version of R.
I think many of our emails back and forth are now posted on the Bioconductor forum.
I might edit this answer with more detailed instructions in the next 24-hours.
The forecast package for R has been updated to version 2.12, but there are currently only windows binarys for 2.11 available on CRAN.
How do I install an R package from the source on Windows?
I know this is an old question but it came up first in my Google search for this same question, even though I knew the answer I just wanted something to copy and paste. Which makes it worth improving the answer for future reference. So here is what works for me:
Install rtools, then:
install.packages(path_to_file, repos = NULL, type="source")
Two answers that may help you avoid the hassle of installing Rtools.
Use http://win-builder.r-project.org/ to build a binary version, download it, and install (using install.packages(...,repos=NULL))
If the package has no binary component (i.e. no src directory with C, C++, or Fortran code that needs to be compiled during installation (not true for forecast, but possibly useful some other time) then simply specifying type="source" within the install.packages call (whether from a repository or a local copy of the source tarball (.tar.gz file)) will install the source package, even on Windows.
Start by reviewing the section on Windows packages in the R Installation and Administration manual, then carefully follow the instructions from The Windows toolset appendix.
I know it's usually bad form to mainly provide links in an answer, but these are links to the canonical references on this topic. I simply link to them rather than summarize their contents, since they should be accurate for the most current R release.
I'm not sure if this is the best way, but I found the following method to work (based in part on the answers above):
1) Download the package .tar
2) Move the package to the directory with your user R libraries (e.g., in my case it was "C:/Users/yourUserName/Documents/R/win-library/3.3")
3) Within Rstudio (or elsewhere, probably), run the command... install.packages("packageName.tar", repos=NULL, type="source")
That worked for me at least. Hope it's helpful!
Download the package *.tar.gz.
make sure you have Rtools installed.
Make sure the R and Rtools paths are added in the environment varialble.
Open a command prompt. Type R CMD INSTALL packagename.tar.gz.
it will work i hope.
To install a package from a .tar.gz file, follow these steps:
Launch R to have the R command prompt
Type: install.packages(<path_to_tar.gz_file>, repos = NULL)
or launch directly:
R CMD INSTALL <path_to_.tar.gz_file>
You need to have R installed but you don't need RTools