.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/hybrid_choice/plot_b01_choice_only_ml.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_hybrid_choice_plot_b01_choice_only_ml.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_hybrid_choice_plot_b01_choice_only_ml.py:


1. Choice model only - maximum likelihood estimation
====================================================

This script runs a **standard discrete choice model** without any latent
variables, estimated by **maximum likelihood** using Biogeme.

It serves as a baseline specification against which hybrid choice models
(with latent variables and measurement equations) can be compared.

The configuration is defined locally in this file and passed to the generic
estimation pipeline via :func:`estimate_model`.

Michel Bierlaire
Thu Dec 25 2025, 08:24:06

.. GENERATED FROM PYTHON SOURCE LINES 17-37




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

 .. code-block:: none

    Default values of the Biogeme parameters are used. 
    File biogeme.toml has been created 
    Results are read from the file saved_results/b01_choice_only_ml.yaml.
    Results for model b01_choice_only_ml
    Nbr of parameters:              7
    Sample size:                    896
    Excluded data:                  0
    Final log likelihood:           -512.5193
    Akaike Information Criterion:   1039.039
    Bayesian Information Criterion: 1072.624

                                  Name     Value  ...  BHHH t-stat.  BHHH p-value
    0                    choice_asc_pt -0.665118  ...     -2.401766      0.016316
    1          choice_beta_time_pt_ref -0.955522  ...     -8.439265      0.000000
    2                 choice_beta_cost -0.079532  ...     -9.546250      0.000000
    3                   choice_asc_car -0.246145  ...     -1.065900      0.286469
    4         choice_beta_time_car_ref -2.033204  ...    -13.104580      0.000000
    5            choice_beta_dist_work -0.204695  ...    -13.801076      0.000000
    6  choice_beta_dist_other_purposes -0.323970  ...    -10.584442      0.000000

    [7 rows x 5 columns]






|

.. code-block:: Python


    import biogeme.biogeme_logging as blog

    from config import Config
    from estimate import estimate_model

    logger = blog.get_screen_logger(level=blog.INFO)

    # Choice model only

    the_config = Config(
        name='b01_choice_only_ml',
        latent_variables="zero",
        choice_model="yes",
        estimation="ml",
        number_of_bayesian_draws_per_chain=20_000,
        number_of_monte_carlo_draws=20_000,
    )

    estimate_model(config=the_config)


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

   **Total running time of the script:** (0 minutes 0.834 seconds)


.. _sphx_glr_download_auto_examples_hybrid_choice_plot_b01_choice_only_ml.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: plot_b01_choice_only_ml.ipynb <plot_b01_choice_only_ml.ipynb>`

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

      :download:`Download Python source code: plot_b01_choice_only_ml.py <plot_b01_choice_only_ml.py>`

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

      :download:`Download zipped: plot_b01_choice_only_ml.zip <plot_b01_choice_only_ml.zip>`


.. only:: html

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

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