.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/assisted/plot_b00logit.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_assisted_plot_b00logit.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_assisted_plot_b00logit.py:


Base model
==========

Logit model.

:author: Michel Bierlaire, EPFL
:date: Thu Jul 13 16:18:10 2023

.. GENERATED FROM PYTHON SOURCE LINES 12-32

.. code-block:: Python


    import biogeme.biogeme as bio
    from biogeme import models
    from biogeme.expressions import Beta
    from IPython.core.display_functions import display

    from biogeme.data.swissmetro import (
        read_data,
        CHOICE,
        SM_AV,
        CAR_AV_SP,
        TRAIN_AV_SP,
        TRAIN_TT_SCALED,
        TRAIN_COST_SCALED,
        SM_TT_SCALED,
        SM_COST_SCALED,
        CAR_TT_SCALED,
        CAR_CO_SCALED,
    )








.. GENERATED FROM PYTHON SOURCE LINES 33-34

Parameters to be estimated.

.. GENERATED FROM PYTHON SOURCE LINES 34-39

.. code-block:: Python

    ASC_CAR = Beta('ASC_CAR', 0, None, None, 0)
    ASC_TRAIN = Beta('ASC_TRAIN', 0, None, None, 0)
    B_TIME = Beta('B_TIME', 0, None, None, 0)
    B_COST = Beta('B_COST', 0, None, None, 0)








.. GENERATED FROM PYTHON SOURCE LINES 40-41

Definition of the utility functions.

.. GENERATED FROM PYTHON SOURCE LINES 41-45

.. code-block:: Python

    V1 = ASC_TRAIN + B_TIME * TRAIN_TT_SCALED + B_COST * TRAIN_COST_SCALED
    V2 = B_TIME * SM_TT_SCALED + B_COST * SM_COST_SCALED
    V3 = ASC_CAR + B_TIME * CAR_TT_SCALED + B_COST * CAR_CO_SCALED








.. GENERATED FROM PYTHON SOURCE LINES 46-47

Associate utility functions with the numbering of alternatives.

.. GENERATED FROM PYTHON SOURCE LINES 47-49

.. code-block:: Python

    V = {1: V1, 2: V2, 3: V3}








.. GENERATED FROM PYTHON SOURCE LINES 50-51

Associate the availability conditions with the alternatives.

.. GENERATED FROM PYTHON SOURCE LINES 51-53

.. code-block:: Python

    av = {1: TRAIN_AV_SP, 2: SM_AV, 3: CAR_AV_SP}








.. GENERATED FROM PYTHON SOURCE LINES 54-56

Definition of the model. This is the contribution of each
observation to the log likelihood function.

.. GENERATED FROM PYTHON SOURCE LINES 56-58

.. code-block:: Python

    logprob = models.loglogit(V, av, CHOICE)








.. GENERATED FROM PYTHON SOURCE LINES 59-60

Read the data

.. GENERATED FROM PYTHON SOURCE LINES 60-62

.. code-block:: Python

    database = read_data()








.. GENERATED FROM PYTHON SOURCE LINES 63-64

Create the Biogeme object.

.. GENERATED FROM PYTHON SOURCE LINES 64-69

.. code-block:: Python

    the_biogeme = bio.BIOGEME(database, logprob)
    the_biogeme.modelName = 'b00logit'
    the_biogeme.generate_html = False
    the_biogeme.generate_pickle = False





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

 .. code-block:: none

    File biogeme.toml has been created




.. GENERATED FROM PYTHON SOURCE LINES 70-71

Calculate the null log likelihood for reporting.

.. GENERATED FROM PYTHON SOURCE LINES 71-73

.. code-block:: Python

    the_biogeme.calculate_null_loglikelihood(av)





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

 .. code-block:: none


    np.float64(-11093.62734528626)



.. GENERATED FROM PYTHON SOURCE LINES 74-75

Estimate the parameters

.. GENERATED FROM PYTHON SOURCE LINES 75-77

.. code-block:: Python

    results = the_biogeme.estimate()








.. GENERATED FROM PYTHON SOURCE LINES 78-80

.. code-block:: Python

    print(results.short_summary())





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

 .. code-block:: none

    Results for model b00logit
    Nbr of parameters:              4
    Sample size:                    10719
    Excluded data:                  9
    Null log likelihood:            -11093.63
    Final log likelihood:           -8670.164
    Likelihood ratio test (null):           4846.927
    Rho square (null):                      0.218
    Rho bar square (null):                  0.218
    Akaike Information Criterion:   17348.33
    Bayesian Information Criterion: 17377.45





.. GENERATED FROM PYTHON SOURCE LINES 81-82

Get the results in a pandas table

.. GENERATED FROM PYTHON SOURCE LINES 82-84

.. code-block:: Python

    pandas_results = results.get_estimated_parameters()
    display(pandas_results)




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

 .. code-block:: none

                  Value  Rob. Std err  Rob. t-test  Rob. p-value
    ASC_CAR    0.015903      0.037081     0.428887      0.668006
    ASC_TRAIN -0.652484      0.054375   -11.999761      0.000000
    B_COST    -0.789434      0.050943   -15.496572      0.000000
    B_TIME    -1.277788      0.065558   -19.490834      0.000000





.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.966 seconds)


.. _sphx_glr_download_auto_examples_assisted_plot_b00logit.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_b00logit.ipynb <plot_b00logit.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_b00logit.py <plot_b00logit.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_b00logit.zip <plot_b00logit.zip>`


.. only:: html

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

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