.. image:: pystat.png
    :height: 20
    :alt: Statistique
    :target: http://www.xavierdupre.fr/app/ensae_teaching_cs/helpsphinx/td_2a_notions.html#pour-un-profil-plutot-data-scientist

Timeseries - Filtre de Kalman
+++++++++++++++++++++++++++++

*(à venir)*

*Lectures*

* `An Introduction to the Kalman Filter <http://www.cs.unc.edu/~welch/media/pdf/kalman_intro.pdf>`_
* `Implementation of Kalman Filter with Python Language <https://arxiv.org/ftp/arxiv/papers/1204/1204.0375.pdf>`_
* `Derivation of Kalman Filtering and Smoothing Equations <https://users.ece.cmu.edu/~byronyu/papers/derive_ks.pdf>`_
* `Auto-Differentiating Linear Algebra <https://arxiv.org/pdf/1710.08717.pdf>`_
* `Kalman Filtering in Python for Reading Sensor Input <http://scottlobdell.me/2014/08/kalman-filtering-python-reading-sensor-input/>`_
* `kalman 2d filter in python <https://stackoverflow.com/questions/13901997/kalman-2d-filter-in-python>`_
* `Multidimensional Kalman-Filter <https://github.com/balzer82/Kalman>`_
* `Deep Kalman Filters <https://arxiv.org/abs/1511.05121>`_
* `Nonparametric Risk Bounds for Time-Series Forecasting <http://jmlr.org/papers/volume18/13-336/13-336.pdf>`_
* `The Kalman Filter and (Maximum) Likelihood <https://towardsdatascience.com/the-kalman-filter-and-maximum-likelihood-9861666f6742>`_
  (article contenant du code avec :epkg:`statsmodels` avec la réécriture d'un modèle :epkg:`ARMA`
  sous la forme d'un filtre de Kalman inspiré de
  `State-Space Models <http://www-stat.wharton.upenn.edu/~stine/stat910/lectures/14_state_space.pdf>`_)

*Modules*

* `pykalman <https://pykalman.github.io/>`_
* `filterpy <https://github.com/rlabbe/filterpy>`_
* `scipy <http://scipy-cookbook.readthedocs.io/items/KalmanFiltering.html>`_
* `kalman-filter <https://github.com/hbcbh1999/kalman-filter>`_