I'm trying to use R through SPSS syntax (I'm using SPSS 18 on windows 7) which requires installing a special plugin: PASWStatistics_RPlugIn_1802_win32.exe. Also I had to install an older version of R(2.8.1 - required by my older version of SPSS - i like it better than the new ones). The plugin now works, R (both versions) works, but Rstudio stopped working and won't start even after uninstalling and re-installing.
Does anyone have any similar experience and could suggest a solution?
The following link specifies how you can configure Rstudio to work with a specific R version you have installed:
http://www.rstudio.com/ide/docs/advanced/versions_of_r
Just install R 2.8 and 2.14 and let spss use one, and Rstudio another.
You are taking a risk by using old versions of spss and R (bugs that have been fixed in newer versions, decreased performance, possible incompatibility with other software e.g. R packages, missing functionality).
You can have multiple versions of R installed at the same time - I have five. The current version of Statistics, 21, goes with R2.14. I don't know how Rstudio determines which version to use. You might need to reset the R environment variables or your path settings.
Related
I am using the regular R console on a MAC Air with Monterrey as the OS and I'm still having issues loading packages. It is iffy, as to whether a package is loaded and ready to use. Sometimes packages will load and sometimes not. Also, it would not call up data sets that as a default are included in the R packages I'm trying to use. the weird thing is it would recognize the example dataset that is included because when I first tied to call them up, it would let me autocomplete the name. Then it stopped doing that. Then it started telling me that the file doesn't exist. I know I haven't used R in a while but this just seems buggy! any help would be appreciated.
The R version that I have installed is : R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics" and it was installed just last week.
It seems R was not properly installed on your machine.
Several persons reported that using the package manager in RStudio actually did the trick of updating the packages.
I recently installed R 4.0, after previously using relying R 3.6.3. To manage R repositories, I use Rstudio (currently 1.2.5042 on a Windows 10 machine). After upgrading to R 4.0, I opened a project from a few months ago, and realized that Rstudio is now, by default, using the newer version of R (and it's library folder). When running renv::restore(), renv attempts to re-install all libraries in the .lock file for the newer version of R, and I don't see any way to specify that I want to keep using R 3.6.3 and it's associated library.
Coming from a python background, I had assumed that renv would create a virtual environment that isolates both the interpreter and the libraries that the project uses (similar to how anaconda environments are created). However, after looking through the documentation and doing a few searches, I have found no reference to isolating a particular version of R. I have, however, found that Rstudio defaults to using the latest version of R, which is not necessarily the behaviour that I want.
I have tried using anaconda to manage an R environment. However, Anaconda relies on its own smaller repository of R packages, and many of the libraries I need are from researchers that house their code on GitHub.
Is there a way to create an R environment in which I can isolate both the R libraries and the version of R itself? Or, perhaps there is something I am missing about how environments with R/Rstudio are intended to be used?
You are correct that renv only manages the installed R packages, and not the R interpreter itself.
Depending on how you're using RStudio, you can still "fake" this by setting the RSTUDIO_WHICH_R environment variable. For example:
export RSTUDIO_WHICH_R=/path/to/R
rstudio
would tell RStudio to "bind" to the version of R specified by the RSTUDIO_WHICH_R environment variable.
For what it's worth, the ability to bind projects to a specific version of R is a feature of the professional editions of RStudio; however, it's not available in the open-source version. See here for more details.
I am running R 3.6.1 on a Mac Mini running Sierra and a MacBook Pro running El Capitan. I normally get all the R packages that I need from CRAN or github and use them without issues, but I am trying to install and use an R package (NicheMapR) that requires a fortran compiler and this is giving me issues. Even after installing gfortran, the R package still does not work (the fortran code seems to be compiled but the package installation fails). The package developer suggested that installing R via homebrew might solve the problem. On the contrary, my hunch is that it would lead to a world of pain, to quote Walter from the Big Lebowski. My questions are:
What is the advantage of a homebrew version of R for MacOSX over the "regular" version installed from CRAN?
Can the two versions coexist?
Is the homebrew version going to affect the regular one?
Finally: is homebrew going to help or will it simply open a whole
new can of worms?
Many thanks in advance.
Yes, installing from homebrew is a recipe for pain. It's specifically recommended against by the official CRAN binary maintainer see his remarks from March 2016 on r-sig-mac.
Regarding your questions, this can be summarized as:
What is the advantage of a homebrew version of R for MacOSX over the "regular" version installed from CRAN?
Positives: Select your own BLAS and easily work with geospatial tools.
Downsides: Always needing to compile each R package.
Can the two versions coexist?
Yes. The homebrew version installs into a different directory. But, watch out for library collision (see next question). However, you will have to deal with symbolic linking regarding what version of R is accessible from the console and you will also need to look into using RSwitch to switch between R versions.
Is the homebrew version going to affect the regular one?
Yes, if the library paths overlap. There will be problems regarding package installation and loading. Make sure to setup different library paths. To do so, please look at the .libPaths() documentation.
Finally: is homebrew going to help or will it simply open a whole new can of worms?
Yes and no. Unless you know what you're doing, opt for the CRAN version of R and its assorted goodies.
I feel pretty comfortable working with R, and I want to get into Python through Anaconda.
Upon trying the Jupyter Notebook and finding it has compatibility with R, I really want to use it.
I'm having problem installing the R packages that don't come in R-essentials; and mainly because I noticed it uses a different R installation than the one I had before. Not only is this a different R installation, but it also uses a previous version of R. In my local installation I have updated to 3.2.3 but in the Anaconda environment for Jupyter I got 3.1.
I also found a post to change the .libPaths variable to include the packages that I had already installed. Still, I see this as a potential problem because of the different R versions.
I wanted to know if I can update the R version that's used in Anaconda, or if I can point to the one that's installed locally.
Thank you.
You can install IRkernel in the normal R installation and then register the kernel: simply follow the instructions at http://irkernel.github.io/installation/
I have updated my R to the latest version, that is R version 3.1.0 beta (2014-03-28 r65330). My problems is that ggplot2 does not have a version that supports this R.
How can I fix this issue? I mean I guess I need to install an earlier version of R, but apart from this, which refers to Windows I hadn't found any specific way to install an older version.
UPDATE
#Yilun Zhang I cannot find the place where I should change the R version. Where should it be:
Just try again or tomorrow.
You ended up with a (March 28) prerelease of R 3.1.0 which came today (April 10). The CRAN mirrors were not yet set up for this (at that point: unreleased) version 3.1.0. They are now. You should find ggplot2.
If you are using RStudio and have the older r version:
go to the navigation bar
go to tools
Global options
there is a section where you can choose the r version
If you are using just the R console, just go to the old r directory and open it.