Does anyone know if this is an error on #CRAN? I went to install the {multcompView} package only to have the error returned:
package ‘multicompView’ is not available for this version of R
So I naturally checked on CRAN what version of R it Depends on, and to my suprise, nothing was listed 🤔 I would have thought listing the R version under Depends would be a hard requirement and would have failed CRAN checks otherwise. #RStats https://cran.r-project.org/web/packages/multcompView/index.html
I have an #rstats#cran question. If I document an unexported function, will CRAN reject me if I don't include #' @examples for each of the functions (like they would do for an exported function)?
The {ggsurvfit} package made its v1.0 release! 🕺🏻🕺🏻
Check it out for your survival/time-to-event visualization needs! The plots are fully ggplot and integrate seamlessly with all the ggplot functions you you already know 📈
For 5 years, the ROracle #rstats package provided by #Oracle to CRAN has been broken on Windows. Some nice fellow has finally caved and posted a fork that actually works. Good for him! But it exposes an underlying problem,
@obrl_soil
As much as I don't like Oracle (mostly because of what they have done in the past), I havet o agree that CRAN's review process suffers from single-person-blockage. All your submissions come down to decision of one person. The #rOpenSci process is more democratic and way more transparent, but it is excruciatingly lengthy. I personally like a middle ground approach (transparent communication, more than one moderator for package submission, quick responses)
New releases of the #rstats packages {dqrng} and {tikzDevice} have made it unto #CRAN. While the latter release has only minor internal changes, dqrng now comes with two new functions dqrrademacher for drawing Rademacher weights and dqrmvnorm for drawing from a multivariate normal distribution.
In addition, the C++ templates used by the fast sampling methods are now in their own header file allowing for parallel usage.
What does the network of people with common package contributions look like?
And much more!
There are also interactive {gt} tables so you can browse contribution and package statistics; and I’ve shared the data so you can explore your own questions. Enjoy!