.. _sphx_glr_auto_examples_hybrid_choice:

Biogeme examples for hybrid choice models
*****************************************

This directory provides example implementations of MIMIC and hybrid
choice models estimated with Biogeme, using both maximum likelihood
and Bayesian methods. The examples range from latent-variable-only
models to fully integrated hybrid choice models and are intended as
reproducible references and learning material.





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    <div class="sphx-glr-thumbnails">

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    <div class="sphx-glr-thumbcontainer" tooltip="Choice model specification with optional latent-variable interactions.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_choice_model_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_choice_model.py`

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      <div class="sphx-glr-thumbnail-title">Choice model</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Central configuration for running estimation scripts.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_config_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_config.py`

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      <div class="sphx-glr-thumbnail-title">Configuration</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Estimation pipeline for discrete and hybrid choice models.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_estimate_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_estimate.py`

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      <div class="sphx-glr-thumbnail-title">Model estimation</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Generate SLURM .run job scripts for batch execution on the JED cluster.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_generate_jed_run_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_generate_jed_run.py`

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      <div class="sphx-glr-thumbnail-title">Prepare for server</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Definitions of latent variables used in the hybrid choice model.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_latent_variables_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_latent_variables.py`

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      <div class="sphx-glr-thumbnail-title">Latent variables</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Definition of Likert indicators and Likert scale types used in the hybrid choice model.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_likert_indicators_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_likert_indicators.py`

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      <div class="sphx-glr-thumbnail-title">Likert indicators</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Construction of the MIMIC (latent-variable) component of the hybrid choice model.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_mimic_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_mimic.py`

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      <div class="sphx-glr-thumbnail-title">MIMIC model</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Optima data preparation for Biogeme.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_optima_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_optima.py`

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      <div class="sphx-glr-thumbnail-title">Data preparation</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="This script runs a standard discrete choice model without any latent variables, estimated by maximum likelihood using Biogeme.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_plot_b01_choice_only_ml_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_plot_b01_choice_only_ml.py`

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      <div class="sphx-glr-thumbnail-title">1. Choice model only - maximum likelihood estimation</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="This script estimates a pure MIMIC model (measurement and structural components only) using maximum likelihood, without an associated discrete choice model.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_plot_b02_mimic_ml_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_plot_b02_mimic_ml.py`

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      <div class="sphx-glr-thumbnail-title">2. MIMIC model - maximum likelihood estimation</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="This script estimates a hybrid choice model that combines:">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_plot_b03_hybrid_ml_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_plot_b03_hybrid_ml.py`

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      <div class="sphx-glr-thumbnail-title">3. Hybrid choice model - maximum likelihood estimation</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="This script estimates a standard discrete choice model without any latent variables using Bayesian estimation in Biogeme.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_plot_b04_choice_only_bayes_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_plot_b04_choice_only_bayes.py`

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      <div class="sphx-glr-thumbnail-title">4. Choice model only - Bayesian estimation</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="This script estimates a pure MIMIC model (latent-variable structural and measurement equations only) using Bayesian estimation in Biogeme, without an associated discrete choice model.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_plot_b05_mimic_bayes_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_plot_b05_mimic_bayes.py`

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      <div class="sphx-glr-thumbnail-title">5. MIMIC model - Bayesian estimation</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="This script estimates the full hybrid choice model, combining:">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_plot_b06_hybrid_bayes_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_plot_b06_hybrid_bayes.py`

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      <div class="sphx-glr-thumbnail-title">6. Hybrid choice model - Bayesian estimation</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Utility functions to either read previously estimated parameters from disk or run a new estimation if no results are available.">

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  .. image:: /auto_examples/hybrid_choice/images/thumb/sphx_glr_read_or_estimate_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_hybrid_choice_read_or_estimate.py`

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      <div class="sphx-glr-thumbnail-title">Read or estimate model parameters</div>
    </div>


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.. toctree::
   :hidden:

   /auto_examples/hybrid_choice/choice_model
   /auto_examples/hybrid_choice/config
   /auto_examples/hybrid_choice/estimate
   /auto_examples/hybrid_choice/generate_jed_run
   /auto_examples/hybrid_choice/latent_variables
   /auto_examples/hybrid_choice/likert_indicators
   /auto_examples/hybrid_choice/mimic
   /auto_examples/hybrid_choice/optima
   /auto_examples/hybrid_choice/plot_b01_choice_only_ml
   /auto_examples/hybrid_choice/plot_b02_mimic_ml
   /auto_examples/hybrid_choice/plot_b03_hybrid_ml
   /auto_examples/hybrid_choice/plot_b04_choice_only_bayes
   /auto_examples/hybrid_choice/plot_b05_mimic_bayes
   /auto_examples/hybrid_choice/plot_b06_hybrid_bayes
   /auto_examples/hybrid_choice/read_or_estimate