Great news for #reproducibility, and a more modern feel to navigating old and current versions of R packages: #RStudio's Package Manager.
packagemanager.rstudio.com
#RStats @rstats

@stragu @rstats

Thanks for sharing the information on the #RStudio package manager.
This seems to be a quite high-level way to achieve #reproducibility as it requires a rstudio package manager server for it.

What is the best (low-level) solution to achieve reproducibility with #Rstats? For example, how can I ensure that my analysis (datasets and R syntax) still runs and reproduces the very same results in - let's say- 7 years from now?

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@gerald_leppert
Low level: Make a copy of R (or just the installer) and the current library folder. Set your scripts to use that folder with .libPaths() at the very beginning.

@stragu @rstats

@koantig @gerald_leppert @rstats If you don't want to rely on a server, I think the most straight-forward solution for self-contained, reproducible projects that include specific package versions would be to use packrat: rstudio.github.io/packrat/

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