Multiple Inference: A Python package for comparing multiple parameters

Scientists often want to compare many parameters. For example, scientists often run randomized control trials to study the effects of many treatments, use observational data to compare many geographic regions, and study how public policy will impact many subgroups of people. multiple-inference implements many of the latest econometric and statistical tools for making such comparisons, including inference after ranking, simultaneous confidence sets, and Bayesian estimators. It uses a statsmodels-like API and provides template notebooks for ease of use. In just a few clicks, researchers can upload a .csv file of conventional estimates (e.g., ordinary least squares or instrumental variables estimates) to a Jupyter binder and click "run" to apply a suite of multiple inference tools to their data.