“Editorial” published in The R Journal.
On behalf of the editorial board, I am pleased to present Volume 14 Issue 2 of the R Journal.
First, some news about the journal board. Mark van der Loo has very kindly agreed to move from Associate Editor to Executive Editor to fill a temporary gap. One new Associate Editor, Kevin Burke, has recently joined the team.
Behind the scenes, several people are assisting with the journal operations and the new developments. Mitchell O’Hara-Wild continues to work on infrastructure, and H. Sherry Zhang continues to develop the rjtools package. In addition, articles in this issue have been carefully copy edited by Hannah Comiskey.
There are also exciting new efforts in developing software to convert the legacy papers from latex to Rmarkdown, and hence create an html version to complement the pdf. Abhishek Ulayil, funded by the 2022 Google Summer of Code project, supervised by Heather Turner and Di Cook, with collaboration from Christophe Dervieux and Mitch O’Hara-Wild, has created the R package, texor, https://abhi-1u.github.io/texor/. It converts the legacy latex style into to the new Rmarkdown template, as would be given with the rjtools package. This package will be used to slowly, and steadily convert as many past articles into an html version.
If you are currently only a latex author, the texor package will get your paper into an Rmarkdown paper, doing the hard-work of the conversion. This is a good opportunity to get a head start on learning how to make reproducible documents. Reproducible documents keeps your code and results in the same place, and reduces the chance of getting them out of sync. Going forwards with the R Journal there will be a growing emphasis on receiving papers in Rmarkdown (and Quarto, at some point) format, because it is easier to test the code, and it makes the work more accessible to readers.
News from the CRAN, the R Foundation and the Forwards Taskforce are included in this issue. We also have a report from the Why R? Turkey 2022 conference.
This issue features 18 contributed research articles the majority of which relate to R packages for modelling tasks. All packages are available on CRAN. Topics covered are: