A cohesive set of open-source tools for working with probability distributions, uncertainty, and reproducible statistical workflows.
Install with R by running
install.packages("probaverse")
The foundation of the probaverse, `distionary` makes probability distributions tangible with a flexible, generic framework. It offers a simple interface for evaluating …
When I was modelling streamflow for the Coldwater River in British Columbia, I needed to combine distributions for rainfall-driven flow and snowmelt-driven flow. In that case, one useful operation was to take the distribution of whichever component was larger.
In the release of distplyr, I wrote about needing to modify probability distributions to make them realistic for applications. Once distplyr made that possible along with distionary, I still needed to tune those distributions based on data.
The core probaverse package, distionary, has been published to CRAN! It defines the “probability distribution” object and provides infrastructure for their evaluation. Learn more on the blog post on the rOpenSci website.
