.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/hybrid_choice/plot_b02_mimic_ml.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_hybrid_choice_plot_b02_mimic_ml.py: 2. MIMIC model - maximum likelihood estimation ============================================== This script estimates a **pure MIMIC model** (measurement and structural components only) using **maximum likelihood**, without an associated discrete choice model. It is mainly intended to: - test and validate the latent-variable specification, - assess identification and normalization issues, and - serve as a building block for hybrid choice models. The model configuration is defined locally in this file and passed to the generic estimation pipeline via :func:`estimate_model`. Michel Bierlaire Thu Dec 25 2025, 08:24:35 .. GENERATED FROM PYTHON SOURCE LINES 21-39 .. rst-class:: sphx-glr-script-out .. code-block:: none Biogeme parameters read from biogeme.toml. Results are read from the file saved_results/b02_mimic_ml.yaml. Results for model b02_mimic_ml Nbr of parameters: 60 Sample size: 896 Excluded data: 0 Final log likelihood: -17009.57 Akaike Information Criterion: 34139.14 Bayesian Information Criterion: 34427.01 Name ... BHHH p-value 0 measurement_intercept_Mobil12 ... 1.690337e-01 1 measurement_coefficient_environmental_attitude... ... 2.727652e-02 2 struct_environmental_attitude_childSuburb ... 1.148750e-02 3 struct_environmental_attitude_ScaledIncome ... 7.110204e-04 4 struct_environmental_attitude_city_center_as_kid ... 3.886242e-02 5 struct_environmental_attitude_artisans ... 2.878049e-02 6 struct_environmental_attitude_high_education ... 2.373663e-03 7 struct_environmental_attitude_low_education ... 1.418459e-01 8 struct_environmental_attitude_sigma_log ... 1.220268e-08 9 measurement_Mobil12_sigma_log ... 1.069770e-01 10 likert_delta_0_log ... 0.000000e+00 11 likert_delta_1_log ... 9.663676e-07 12 measurement_intercept_Mobil09 ... 9.279196e-05 13 measurement_coefficient_car_centric_attitude_M... ... 4.853264e-07 14 struct_car_centric_attitude_high_education ... 2.101643e-05 15 struct_car_centric_attitude_top_manager ... 2.798325e-01 16 struct_car_centric_attitude_employees ... 4.544281e-01 17 struct_car_centric_attitude_age_30_less ... 4.424488e-03 18 struct_car_centric_attitude_ScaledIncome ... 6.771161e-01 19 struct_car_centric_attitude_car_oriented_parents ... 1.164681e-03 20 struct_car_centric_attitude_sigma_log ... 9.493466e-02 21 measurement_Mobil09_sigma_log ... 2.856044e-04 22 measurement_intercept_Envir03 ... 2.936380e-04 23 measurement_coefficient_environmental_attitude... ... 3.837000e-09 24 measurement_Envir03_sigma_log ... 1.155933e-01 25 measurement_intercept_Envir05 ... 1.604078e-02 26 measurement_coefficient_environmental_attitude... ... 0.000000e+00 27 measurement_Envir05_sigma_log ... 4.060020e-06 28 measurement_intercept_Envir04 ... 1.975210e-03 29 measurement_coefficient_environmental_attitude... ... 2.220446e-16 30 measurement_Envir04_sigma_log ... 7.405030e-06 31 measurement_intercept_Mobil05 ... 3.136052e-03 32 measurement_coefficient_car_centric_attitude_M... ... 6.612856e-05 33 measurement_Mobil05_sigma_log ... 7.029157e-01 34 measurement_intercept_Mobil10 ... 5.597204e-02 35 measurement_coefficient_car_centric_attitude_M... ... 1.153146e-02 36 measurement_Mobil10_sigma_log ... 3.266098e-01 37 measurement_intercept_LifSty07 ... 3.301369e-01 38 measurement_coefficient_car_centric_attitude_L... ... 4.580834e-02 39 measurement_LifSty07_sigma_log ... 4.474957e-01 40 measurement_coefficient_environmental_attitude... ... 1.418943e-04 41 measurement_intercept_Mobil03 ... 5.909451e-04 42 measurement_coefficient_car_centric_attitude_M... ... 1.028528e-04 43 measurement_Mobil03_sigma_log ... 6.745101e-02 44 measurement_intercept_NbCar ... 0.000000e+00 45 measurement_coefficient_car_centric_attitude_N... ... 1.839200e-09 46 cars_delta_1_log ... 0.000000e+00 47 cars_delta_2_log ... 0.000000e+00 48 measurement_coefficient_car_centric_attitude_E... ... 1.598542e-07 49 measurement_Envir02_sigma_log ... 1.188719e-06 50 measurement_intercept_LifSty01 ... 1.181660e-01 51 measurement_coefficient_environmental_attitude... ... 1.969394e-04 52 measurement_LifSty01_sigma_log ... 7.193841e-03 53 measurement_intercept_Mobil08 ... 2.167058e-01 54 measurement_coefficient_car_centric_attitude_M... ... 3.447992e-04 55 measurement_Mobil08_sigma_log ... 6.359053e-01 56 measurement_intercept_Envir06 ... 2.326318e-05 57 measurement_coefficient_car_centric_attitude_E... ... 3.092209e-02 58 measurement_coefficient_environmental_attitude... ... 0.000000e+00 59 measurement_Envir06_sigma_log ... 8.213430e-13 [60 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) the_config = Config( name='b02_mimic_ml', latent_variables="two", choice_model="no", 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 0.948 seconds) .. _sphx_glr_download_auto_examples_hybrid_choice_plot_b02_mimic_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_b02_mimic_ml.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_b02_mimic_ml.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_b02_mimic_ml.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_