Mailing Lists

Please read the instructions below and the posting guide before sending anything to any mailing list!

Thanks to Martin Maechler (and ETH Zurich), there are five general mailing lists devoted to R.


This list is for major announcements about the development of R and the availability of new code. It has a low volume (typically only a few messages a month) and everyone mildly interested should consider subscribing, but note that R-help gets everything from R-announce as well, so you don’t need to subscribe to both of them.

Note that the list is moderated to be used for announcements mainly by the R Core Development Team. Use the web interface for information, subscription, archives, etc.


The ‘main’ R mailing list, for discussion about problems and solutions encountered using R, including using R packages in the standard R distribution and on CRAN; announcements (not covered by R-announce or R-packages); the availability of new functionality for R and documentation of R; and for posting nice examples and benchmarks.

This is quite an active list with many messages per day. An alternative is to subscribe and choose daily digests (in plain or MIME format). Use the web interface for information, subscription, archives, etc.

Please read the posting guide before sending a message to the list. In particular, if asking for help with a problem, it is important to be clear and concrete, and it is almost always advisable to send a minimal reproducible example of the problem.

There are many more specific R email lists (see below under ‘Special Interest Groups’). If a problem is appropriate for one of the more specific lists, you are usually more likely to get help by posting to the more specific list. For example, a problem specific to R under macOS should normally be posted to the R-SIG-Mac list, and a problem concerning R software for mixed-effects models should normally be posted to the R-SIG-mixed-models list.

R-help is not intended for help with homework or basic-statistics questions.

Bugs in contributed CRAN packages should normally be reported directly to the package maintainer (use maintainer("package-name") in R). You may also be able to obtain help with a problem from the package maintainer.

Help with R problems is available from a number of sources beyond the R email lists. See under ‘Help’ at the R home page.


is to get help about package development in R, i.e., to provide a forum for learning about the package development process, a community of R package developers who can help each other solve problems, and reduce some of the burden on the CRAN maintainers. If you are having problems developing a package or passing R CMD check, this is the place to ask!

There may be some overlap of topics with the R-devel mailing list, as before the existence of R-package-devel, many package developers had used R-devel instead. Beware that cross-posting to both lists is generally considered as impolite. For subscription and more, please read and use the web interface.


This list is intended for questions and discussion about code development in R. Questions likely to prompt discussion unintelligible to non-programmers or topics that are too technical for R-help’s audience should go to R-devel, unless they are specifically about problems in R package development where the R-package-devel list is appropriate, see also the posting guide section. The list is also for proposals of new functionality for R, and pre-testing of new versions. It is meant particularly for those who maintain an active position in the development of R.

If you don’t want to receive more than a daily message, you can subscribe and choose digests (in plain or MIME format). Use the web interface for information, subscription, archives, etc.


This list is for announcements as well, usually on the availability of new or enhanced contributed packages (on CRAN, typically).

Note that the list is moderated. However, CRAN package authors (and others, similarly qualified) can freely post. As with R-announce, all messages to R-packages are automatically forwarded to the main R-help mailing list; we still recommend to subscribe to R-packages if you read R-help only in digest form. Use the web interface for information, subscription, archives, etc.

Special Interest Groups

Additionally, there are several specific Special Interest Group (=: SIG) mailing lists; however do post to only one list at time (‘SIG’ or general one), cross-posting is considered to be impolite.

  • R-SIG-Mac: R Special Interest Group on Mac ports of R

  • R-SIG-DB: R SIG on Database Interfaces

  • R-SIG-Debian: R Special Interest Group for Debian ports of R

  • R-SIG-dynamic-models: Special Interest Group for Dynamic Simulation Models in R

  • R-SIG-ecology: Using R in ecological data analysis

  • R-SIG-Epi: R for epidemiological data analysis

  • R-SIG-Fedora: R Special Interest Group for Fedora and Redhat ports of R

  • R-SIG-Finance: Special Interest Group for ‘R in Finance’

  • R-SIG-Geo: R Special Interest Group on using Geographical data and Mapping

  • R-SIG-gR: R SIG on gRaphical models

  • R-SIG-GUI: R Special Interest Group on GUI Development

  • R-SIG-HPC: R SIG on High-Performance Computing

  • R-SIG-Insurance: Special Interest Group on using R in actuarial science and insurance

  • R-SIG-Jobs: R SIG List for Announcements of Jobs where R is used

  • R-SIG-meta-analysis: R SIG for discussing the use of R for conducting meta-analyses

  • R-SIG-mixed-models: R SIG on Mixed Effect Models, notably lmer() related

  • R-SIG-networks: R SIG for users and developers of network- or graph-related software within R

  • R-SIG-phylo: R SIG on phylogenetic and comparative methods and analyses

  • R-SIG-Robust: R SIG on Robust Statistics

  • R-SIG-teaching: SIG on Teaching Statistics (and more) using R

To satisfy geographic or regional (or subject) needs, some R users have formed “R User Groups” for which there are mailing lists. Information about most of these groups and their lists can be found on the Revolution page.

Archives and Search Facilities

  • Browsable HTML versions of the mail archives can be found at the web interface.

  • Have a look at CRAN’s search page for searchable versions of the mailing list archives.

General Instructions

Note that you should configure your e-mail software in such a way as to send only plain text, i.e., no HTML. ‘html-ified’ messages are usually considerably longer (in bytes!) and harder to filter for spam or viruses. Many of these (e.g. ‘html-only’ ones) are currently spam-filtered or otherwise intercepted completely and without notice to the sender. For more details and instructions on turning off HTML for your e-mail software, see here or there.

Furthermore, most binary e-mail attachments are not accepted, i.e., they are removed from the posting completely. As an exception, we allow application/pdf, application/postscript, and image/png (and x-tar and gzip on R-devel). You can use text/plain as well, or simply paste text into your message instead.

Information about the list can be obtained by sending an email with info as its contents to Note that you can subscribe and unsubscribe by E-mail (instead of the web interface), but to unsubscribe you currently need the mailing list password which you get when subscribing and in a monthly reminder.

To send a message to everyone on the R-help mailing list, send email to Do please create a new email message when posting to the list rather than replying to a previous message and simply changing the subject line! This allows sensible threading in the mailing list archives (and many users e-mail readers). Subscription and posting to the other lists is done analogously, with R-help replaced by R-announce and R-devel, respectively. Note that the R-announce list is gatewayed into R-help, so you don’t need to subscribe to both of them.

It is recommended that you send mail to R-help (or R-devel if appropriate) rather than only to the R developers (who are also subscribed to the list, of course). This may save them precious time they can use for constantly improving R, and will typically also result in much quicker feedback for yourself.

Of course, in the case of bug reports it would be very helpful to have code which reliably reproduces the problem, see the entry in the R FAQ.