The probaverse is a suite of tools in R for exploring the full space of possible outcomes in an analysis. It elevates probability distributions as tangible objects that realistically represent your system.
"Uncertainty is inevitable in almost all complex systems, from financial markets to environmental systems to the human body. The probaverse offers a way to accept uncertainty, model it, and use those insights to make smarter, more informed decisions."
The foundation of the probaverse, distionary makes probability distributions tangible with a flexible, generic framework. It offers a simple interface for evaluating distributions, defining families based on parameters, and customizing your own distributions and evaluation methods.
Sep 11, 2024
Distributions become alive when they can be transformed. distplyr lets you modify and reshape distributions—whether you're stretching, grafting, maximizing, or something else—giving you the tools to create entirely new families of distributions and expand the possibilities of your analysis.
Sep 10, 2024
famish refines a family of distributions to match real-world data or specific characteristics, such as a given mean or dataset. From parameter estimation to maximum likelihood, famish offers tools for selecting the best-fitting distribution for your needs.
Jul 3, 2024
Complex systems often demand insight into multiple variables and their relationships. couple enables you to construct realistic multivariate distributions by combining copulas and univariate distributions, creating a more nuanced picture of interconnected data.
May 11, 2024
Currently, the probaverse can be installed by each package individually, although only three packages are available as prototypes:
remotes::install_github("probaverse/distionary")
remotes::install_github("probaverse/distplyr")
remotes::install_github("probaverse/famish")