Metadata-Version: 2.1
Name: scikit-hts
Version: 0.5.0
Summary: Hierarchical Time Series forecasting
Home-page: UNKNOWN
Author: Carlo Mazzaferro
Author-email: carlo.mazzaferro@gmail.com
License: UNKNOWN
Description: ##########
        scikit-hts
        ##########
        
        Hierarchical Time Series with a familiar API
        
        
        .. image:: https://travis-ci.org/carlomazzaferro/scikit-hts.svg?branch=master
            :target: https://travis-ci.org/carlomazzaferro/scikit-hts
        
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            :target: https://racket.readthedocs.io/en/latest/?badge=latest
            :alt: Documentation Status
                        
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            :target: https://coveralls.io/github/carlomazzaferro/scikit-hts?branch=master
            :alt: Coverage
        
        .. image:: https://pepy.tech/badge/scikit-hts/month
             :target: https://pepy.tech/project/scikit-hts/month
             :alt: Downloads/Month
        
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            :target: https://join.slack.com/t/scikit-hts/shared_invite/zt-d5is54bp-iOeagm7Jv68ZTkjk_zezrA
            :alt: Slack
        
        
        * `MIT License`_
        * Documentation: https://scikit-hts.readthedocs.io/en/latest/
        
        .. _`MIT License`: https://github.com/carlomazzaferro/scikit-hts/blob/master/LICENSE
        
        Overview
        --------
        
        Building on the excellent work by Hyndman [1]_, we developed this package in order to provide a python implementation
        of general hierarchical time series modeling.
        
        
        .. [1] `Forecasting Principles and Practice. Rob J Hyndman and George Athanasopoulos. Monash University, Australia <https://otexts.com/fpp2/>`_.
        
        .. note:: **STATUS**: alpha. Active development, but breaking changes may come.
        
        
        Features
        --------
        
        * Supported and tested on ``python 3.6``, ``python 3.7`` and ``python 3.8``
        * Implementation of Bottom-Up, Top-Down, Middle-Out, Forecast Proportions, Average Historic Proportions,
          Proportions of Historic Averages and OLS revision methods
        * Support for a variety of underlying forecasting models, inlcuding: SARIMAX, ARIMA, Prophet, Holt-Winters
        * Scikit-learn-like API
        * Geo events handling functionality for geospatial data, including visualisation capabilities
        * Static typing for a nice developer experience
        * Distributed training & Dask integration: perform training and prediction in parallel or in a cluster with Dask
        
        Examples
        --------
        
        You can find code usages here: https://github.com/carlomazzaferro/scikit-hts-examples
        
        Roadmap
        -------
        
        * More flexible underlying modeling support
            * [P] AR, ARIMAX, VARMAX, etc
            * [P] Bring-Your-Own-Model
            * [P] Different parameters for each of the models
        * Decoupling reconciliation methods from forecast fitting
            * [W] Enable to use the reconciliation methods with pre-fitted models
        
        | **P**: Planned
        | **W**: WIP
        
        Credits
        -------
        
        This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
        
        .. _Cookiecutter: https://github.com/audreyr/cookiecutter
        .. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
        
        
        
        =======
        History
        =======
        
        0.1.0 (2020-01-02)
        ------------------
        
        * First release on PyPI.
        
        0.2.0 (2018-02-13)
        ------------------
        
        * Major feature implementation and documentation
        * Static typing
        * Testing - 44% coverage
        
        
        0.2.3 (2020-03-28)
        ------------------
        
        * Testing up to 75%
        * Exogenous variable support
        * Extensive docs
        
        
        0.3.0 (2020-03-28)
        ------------------
        
        * Parallel and distributed training
        
        
        0.4.0 (2020-03-28)
        ------------------
        
        * Testing for all reconciliation methods, line coverage > 80%
        
        
        0.4.1 (2020-03-28)
        ------------------
        
        * Python 3.6 support
        
Keywords: scikit-hts
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Provides-Extra: geo
Provides-Extra: prophet
Provides-Extra: dev
Provides-Extra: auto_arima
Provides-Extra: all
Provides-Extra: test
Provides-Extra: distributed
