Clarification needed for different approaches to updating R on a mac (and keeping packages)

Question

For over a year now, I've been afraid to update my version of R for fear of losing the "rgdal" package...which when I first started working with R on my mac (and maybe still?), had to be installed from source/ could not be installed via the package installer from within R. That was complicated and I had to seek help from a more experienced R user than myself in order to get this package which is critical for me.

But I've finally decided that I need to take the risk and update R. I used the following instructions:

#--run in the old version of R
setwd("C:/Temp/")
packages <- installed.packages()[,"Package"]
save(packages, file="Rpackages")

Followed by this in the new version:

#--run in the new version
setwd("C:/Temp/")
load("Rpackages")
for (p in setdiff(packages, installed.packages()[,"Package"]))
install.packages(p)

found in this post:

Painless way to install a new version of R?

This seems to have worked (e.g. I can open up libraries that aren't included in the base install...including rgdal) but I have the following questions in order to better understand this whole process:

1) Is it the case that in following this approach, I essentially saved a list of all the R packages I had previously installed in my old version, then (from within the new version) determined the SET of packages that differed from the set of base libraries in the new version and told R to install packages belonging to this SET?

2) If the above is true, then does this approach negate the need to update my packages after (e.g. by installing them from within the new version, the newest versions are installed)?

3) The other approach that seems to be common out there (and that is recommended in one of the responses to the post above) is to set up things so that all packages get saved to a directory outside of R and then change the settings (in the .Renviron file or whatever the appropriate file is) to always look for packages in this external directory... I'm wondering why this approach is favoured by some people? Is it because this approach means that after updating R everything is just ready to go (e.g. if one is willing to work with un-updated packages)? I'm confused because if one still has to use update.packages() after installing a new version of R, doesn't this just more or less amount to re-installing them? What are the advantages?

4) Are there packages that I need to worry about if I do go the install route (and not the save to external directory then update route)? R did give me a warning that indicates that four of my packages are not available for the latest version (R. 3.0.3). I'm assuming that if I need to use these packages, I must temporarily just revert to an older version of R. Is this all correct?

Thank you in advance for the help!

Answer 1

1) Yes.

2) The newly installed packages will be at the latest version, but there is no harm in running update.packages(ask=FALSE, checkBuilt=TRUE) afterward just be be sure everything is up to date.

3) I've not seen anyone suggest this particular approach, though a similar process is suggested in the R for Windows FAQ that consists of 1) installing the new version 2) copying the packages from the library folder of the old version to the library folder of the new version and 2) running update.packages(checkBuilt=TRUE, ask=FALSE). I don't think there are any clear advantages to doing it this way vs. the installed.packages()... way.

4) All methods under discussion are limited to CRAN packages, so things that you installed from e.g., bioconductor will not be covered. Also packages removed from CRAN will not be covered, you will either have to use an older version of R or build and install them manually.