.. _sphx_glr_auto_examples_example_simple_fit.py:


=======================
Simple auto_arima model
=======================


This is a simple example of how we can fit an ARIMA model in several lines
without knowing anything about our data or optimal hyper parameters.

.. raw:: html

   <br/>




.. image:: /auto_examples/images/sphx_glr_example_simple_fit_001.png
    :align: center


.. rst-class:: sphx-glr-script-out

 Out::

    Fit ARIMA: order=(2, 1, 2) seasonal_order=(1, 0, 1, 12); AIC=2908.451, BIC=2932.482, Fit time=1.065 seconds
    Fit ARIMA: order=(0, 1, 0) seasonal_order=(0, 0, 0, 12); AIC=3049.597, BIC=3055.604, Fit time=0.038 seconds
    Fit ARIMA: order=(1, 1, 0) seasonal_order=(1, 0, 0, 12); AIC=2895.934, BIC=2907.950, Fit time=0.304 seconds
    Fit ARIMA: order=(0, 1, 1) seasonal_order=(0, 0, 1, 12); AIC=2917.891, BIC=2929.907, Fit time=0.520 seconds
    Fit ARIMA: order=(1, 1, 0) seasonal_order=(0, 0, 0, 12); AIC=3039.240, BIC=3048.252, Fit time=0.013 seconds
    Fit ARIMA: order=(1, 1, 0) seasonal_order=(2, 0, 0, 12); AIC=2890.929, BIC=2905.949, Fit time=3.189 seconds
    Fit ARIMA: order=(1, 1, 0) seasonal_order=(2, 0, 1, 12); AIC=2892.498, BIC=2910.522, Fit time=4.793 seconds
    Fit ARIMA: order=(0, 1, 0) seasonal_order=(2, 0, 0, 12); AIC=2906.911, BIC=2918.927, Fit time=2.095 seconds
    Fit ARIMA: order=(2, 1, 0) seasonal_order=(2, 0, 0, 12); AIC=2873.301, BIC=2891.325, Fit time=4.597 seconds
    Fit ARIMA: order=(2, 1, 1) seasonal_order=(2, 0, 0, 12); AIC=2891.288, BIC=2912.316, Fit time=6.511 seconds
    Fit ARIMA: order=(3, 1, 1) seasonal_order=(2, 0, 0, 12); AIC=2881.360, BIC=2905.391, Fit time=8.597 seconds
    Fit ARIMA: order=(2, 1, 0) seasonal_order=(1, 0, 0, 12); AIC=2879.303, BIC=2894.322, Fit time=0.579 seconds
    Fit ARIMA: order=(2, 1, 0) seasonal_order=(2, 0, 1, 12); AIC=2875.058, BIC=2896.086, Fit time=8.207 seconds
    Fit ARIMA: order=(3, 1, 0) seasonal_order=(2, 0, 0, 12); AIC=2866.267, BIC=2887.294, Fit time=8.301 seconds
    Fit ARIMA: order=(4, 1, 1) seasonal_order=(2, 0, 0, 12); AIC=2870.532, BIC=2897.567, Fit time=10.208 seconds
    Fit ARIMA: order=(3, 1, 0) seasonal_order=(1, 0, 0, 12); AIC=2870.467, BIC=2888.491, Fit time=0.789 seconds
    Fit ARIMA: order=(3, 1, 0) seasonal_order=(2, 0, 1, 12); AIC=2867.919, BIC=2891.951, Fit time=7.218 seconds
    Fit ARIMA: order=(4, 1, 0) seasonal_order=(2, 0, 0, 12); AIC=2858.880, BIC=2882.912, Fit time=10.408 seconds
    Fit ARIMA: order=(5, 1, 1) seasonal_order=(2, 0, 0, 12); AIC=2868.950, BIC=2898.990, Fit time=20.080 seconds
    Fit ARIMA: order=(4, 1, 0) seasonal_order=(1, 0, 0, 12); AIC=2866.318, BIC=2887.345, Fit time=0.806 seconds
    Fit ARIMA: order=(4, 1, 0) seasonal_order=(2, 0, 1, 12); AIC=2863.844, BIC=2890.879, Fit time=25.681 seconds
    Fit ARIMA: order=(5, 1, 0) seasonal_order=(2, 0, 0, 12); AIC=2860.023, BIC=2887.059, Fit time=14.314 seconds
    Total fit time: 138.326 seconds




|


.. code-block:: python

    print(__doc__)

    # Author: Taylor Smith <taylor.smith@alkaline-ml.com>

    import pmdarima as pm
    import numpy as np
    from matplotlib import pyplot as plt

    # #############################################################################
    # Load the data and split it into separate pieces
    data = pm.datasets.load_wineind()
    train, test = data[:150], data[150:]

    # Fit a simple auto_arima model
    arima = pm.auto_arima(train, error_action='ignore', trace=1,
                          seasonal=True, m=12)

    # #############################################################################
    # Plot actual test vs. forecasts:
    x = np.arange(test.shape[0])
    plt.scatter(x, test, marker='x')
    plt.plot(x, arima.predict(n_periods=test.shape[0]))
    plt.title('Actual test samples vs. forecasts')
    plt.show()

**Total running time of the script:** ( 2 minutes  18.431 seconds)



.. only :: html

 .. container:: sphx-glr-footer


  .. container:: sphx-glr-download

     :download:`Download Python source code: example_simple_fit.py <example_simple_fit.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: example_simple_fit.ipynb <example_simple_fit.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_