Hi folks!
I'm really excited to say that the #rstats package {greta} 0.5.0 is approaching release!
{greta} is a simple and scalable statistical modelling in R. You can think of it like writing BUGS/STAN code but using R and not a separate language. It uses Google Tensorflow under the hood, which means it scales well to large data and models.
The main feature of this new release is that we are using Tensorflow 2.0 (TF2) under the hood. This was a pretty big update of the internals, and it wouldn't have been possible without the guidance and direction of Nick Golding, the creator of {greta}. Thanks, Nick!
Outside of the upgrade to TF2, here is a summary of the changes we have made in this release
install_greta_deps()
, I'm pretty confident it should "just work", which is a big call, but I'm keen to hear how it works for you.
For more detail on the changes made in this release, see the NEWS file: https://github.com/greta-dev/greta/blob/master/NEWS.md
If people have time we'd love to get your feedback on trying out the new greta, the easiest way to install it is via the r-universe, with:
install.packages("greta", repos = c("https://greta-dev.r-universe.dev", "https://cloud.r-project.org"))
I am aiming to submit this to CRAN within the next week, ideally by Wednesday 28th August - let me know if you have any feedback or issues with installation and use!
(Also wow, I can write really posts messages on Mastodon)
[#]rstats #bayesian
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For the especially keen, if you'd like to try out our new installation process for managing python dependencies, here are some instructions:
Install greta from the R universe with
install.packages("greta", repos = c("https://greta-dev.r-universe.dev", "https://cloud.r-project.org"))
And then try
library(greta) install_greta_deps()
And follow the prompts for installation.
If all goes well, it should ask you to restart R, after which, you should be able to run
library(greta) # it should do this greta_sitrep()
And it should give you some successful green ticks
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