Data science tools built with a Jax backend.
Project description
statjax
This library is my attempt to compile the data science tools that I use day-to-day in a single place. The main convenience feature over sklearn
or statsmodels
is a port of the Python stargazer
package that can produce latex tables displaying any of the linear models in the package side-by-side. It duplicates part of the statsmodels
GLM functionality, and provides a general GLM class that the user can initialize with an arbitrary link function and oryx
distribution. It also provides a handful of ATE estimators.
All of the models can take array, dataframe/series, or Formulaic
modelmatricies as arguments.
The backend of the package is written in jax
. Overhead is higher, but the package will outperform statsmodels
and sklearn
in large-sample or high-dimensional cases.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.