Metadata-Version: 2.1
Name: parametric-si
Version: 1.0.2
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: Copyright <2021> <TakeuchiLab>
        
        Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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/>`_


