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

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

.. _sphx_glr_auto_examples_hybrid_choice_specs_two_latent_variables_spec.py:


Latent variables (SPEC ONLY)

Pure specification: what depends on what.

Michel Bierlaire
:Wed Mar 04 2026, 13:48:57

.. GENERATED FROM PYTHON SOURCE LINES 9-76

.. code-block:: Python


    from biogeme.latent_variables import (
        LatentVariable,
        PositiveParameterSpec,
        StructuralEquation,
    )

    DEFAULT_SIGMA_START = 10.0

    car_centric_attitude = LatentVariable(
        name="car_centric_attitude",
        structural_equation=StructuralEquation(
            name="car_centric_attitude",
            explanatory_variables=[
                "high_education",
                "top_manager",
                "age_30_less",
                "ScaledIncome",
                "car_oriented_parents",
                "high_education",
                "low_education",
                "male",
                "used_to_go_to_school_by_car",
            ],
        ),
        indicators={
            "Envir01",
            "Envir02",
            "Envir06",
            "Mobil03",
            "Mobil05",
            "Mobil08",
            "Mobil09",
            "Mobil10",
            "LifSty07",
        },
        structural_sigma=PositiveParameterSpec(start=DEFAULT_SIGMA_START),
    )

    environmental_attitude = LatentVariable(
        name="environmental_attitude",
        structural_equation=StructuralEquation(
            name="environmental_attitude",
            explanatory_variables=[
                "childSuburb",
                "ScaledIncome",
                "city_center_as_kid",
                "artisans",
                "high_education",
                "low_education",
                "single",
            ],
        ),
        indicators={
            "Envir01",
            "Envir02",
            "Envir03",
            "Envir04",
            "Envir05",
            "Envir06",
            "Mobil12",
            "LifSty01",
        },
        structural_sigma=PositiveParameterSpec(start=DEFAULT_SIGMA_START),
    )

    latent_variables = [car_centric_attitude, environmental_attitude]


.. _sphx_glr_download_auto_examples_hybrid_choice_specs_two_latent_variables_spec.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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