If you look at the grf package here, you will notice that it has three versions:
It seems that r-devel is the developing version, r-release is the released version and r-olderel is the older version. However, what is weird is that they share the exact same version number 0.10.2. Why don't they change the version number if the versions are different?
Because it's the same version. What that is telling you is that for grf which version is the most up to date if you're using r-devel, or r-release, or r-oldrel. In some cases the versions can be different. For instance if a package just updated and now requires the latest and greatest version of R then the version that shows up in r-oldrel will reflect that those running the previous release (i.e. r-oldrel) will need to use the previous version of the package since they won't be able to install the newest version since it requires the newest version of R.
So in short - those aren't codenames for the version of the package you're looking at. They're referring the version of R.
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I was loading AIMS package and got a warning:
package ‘AIMS’ was built under R version 3.2.0
I thought R-3.1.2 ("Pumpkin Helmet") was the latest release so I checked on CRAN and couldn't see anything about a R-3.2.0.
Before calling it a typo, I googled the "problem" with different keywords and ended on this page from r-project site mentioning two R versions running, a R-release (R-3.1.2) and a "R-devel, to be R-3.2.0".
Googling "r_devel" confirmed what I was guessing, that this is the current development version.
I'm a bit surprised that packages can be built under the development version and I have a twofold question:
- How can a package already be built under a "to be released" R version and is it "safe"?
- Given that the development version is not released yet, how could I use the package with the R version it was built under? (Having a previous R version doesn't prevent me from using the package but I'm not sure I feel comfortable about the warning...)
Or maybe it was really just a typo?...
Some packages need updated version of R (3.2). But sometimes you need a R dependent software which needs former versions (flexarray: R version 2.15). I have both versions installed but the latest installed version is recognized as default. Then I should reinstall R.2.15 for flexarray. Do you have any recommendation to stop reinatallations? Thanks
This question already has answers here:
How should I deal with "package 'xxx' is not available (for R version x.y.z)" warning?
(18 answers)
Closed 8 years ago.
I have R of version 3.0.1 and I have to install Shiny Incubator for that prerequisite is devtools. But i am not able to install both of them as they are not available in given R versions.
"Not available", through install.packages, doesn't actually mean that they're not available - merely that the latest released version isn't compatible with your R version. So, one option is to upgrade, as MrFlick notes - but if you don't have control over your machine (it's remote, say), or you can't upgrade, an alternative is to look in the archive of package versions, and download them from most recent to oldest until you find the one that is compatible.
As an example, let's take devtools. As you can see from the "Depends" field, it needs >= R 3.0.2 - damn! But the archive, containing the old releases, probably has one that's compatible with 3.0.1. Unfortunately the archive doesn't contain compatibility notes, but it does contain dates of release - and we can be fairly sure that versions released prior to R 3.0.2's release won't be designed to work with 3.0.2.
3.0.2 was released in September 2013, and devtools 1.3.0 was released in July. Download it and see if it works. Obviously this may cause problems such as missing functionality that was released in later versions of devtools, but if you can't upgrade, it's better than not having it.
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.
I want to upgrade the package ggplot2:
library(ggplot2)
packageDescription("ggplot2")["Version"]
> 0.8.3
But the current version is 0.8.7.
I tried update.packages(), which seemed to work OK. But it still returned older version 0.8.3.
So I downloaded and installed the package source from Cran, which says 0.8.7 in the download page.
I then install it via the GUI menu in R. It returns
** building package indices ...
* DONE (ggplot2)
I then run:
packageDescription("ggplot2")["Version"]
> 0.8.3
And still I have the older version!
I don't know why this is not working, what's more I had already come across this problem before and solved it (I can't remember exactly what) but now it has gone back to the older version! What's the easiest way to keep packages like this updated automatically and not have them refer back to older packages?
What version of R are you using? CRAN binaries are only kept up-to-date for the latest R release (i.e. 2.10.1). If you have an older version of R and have the development tools installed, you can use install.packages("ggplot2",type="source").
Did you do unloadNamespace('ggplot2')? and the library(ggplot2) and then check the version? Because, once you load a package, it stays in memory of R, even though you might have already installed a newer version of the package, R does not see, until you do the above.