Metadata-Version: 2.1
Name: parametric-si
Version: 1.0.4
Summary: tools for parametric selective inference
Home-page: https://github.com/takeuchi-lab/parametric-si
Author: Takeuchi Lab
Author-email: miwa.daiki.mllab.nit@gmail.com
License: MIT License
Platform: UNKNOWN
License-File: LICENSE

parametric-si
===================================================

This package implements a more powerful and general conditional selective inference(SI) with linear regression.

Key references are the following papers:

    *  `Parametric Programming Approach for More Powerful and General Lasso Selective Inference <https://arxiv.org/abs/2004.09749>`_
    *  `More Powerful and General Selective Inference for Stepwise Feature Selection using the Homotopy Continuation Approach <https://arxiv.org/abs/2012.13545>`_

============
Requirements
============
This package requires the following packages:

* numpy
* scipy
* sklearn
* portion

==============================
Installing parametric_si
==============================
Use pip to install parametric_si package. Required packages will be also installed automatically.

.. code-block:: console
    
    $ pip install parametric_si

=============
API Reference
=============
`Detailed API reference is available here <https://takeuchi-lab.github.io/parametric-si/>`_


