.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/swissmetro/plot_b21multiple_models.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_swissmetro_plot_b21multiple_models.py: .. _plot_b21multiple_models: Assisted specification ====================== Example of the estimation of several versions of the model using assisted specification algorithm. The catalog of specifications is defined in :ref:`plot_b21multiple_models_spec` . All specifications are estimated. Have a look at :ref:`plot_b22multiple_models` for an example where the number of specifications is too high to be enumerated. :author: Michel Bierlaire, EPFL :date: Wed Apr 12 16:58:49 2023 .. GENERATED FROM PYTHON SOURCE LINES 17-26 .. code-block:: default import biogeme.biogeme_logging as blog from biogeme.results import compile_estimation_results from biogeme.multiobjectives import loglikelihood_dimension from biogeme.assisted import AssistedSpecification from plot_b21multiple_models_spec import the_biogeme, PARETO_FILE_NAME logger = blog.get_screen_logger(blog.INFO) logger.info('Example b21multipleModels') .. rst-class:: sphx-glr-script-out .. code-block:: none income_segmentation=INCOME: [{0: 'inc-zero', 1: 'inc-under50', 2: 'inc-50-100', 3: 'inc-100+', 4: 'inc-unknown'}] ref: inc-zero Total number of possible specifications: 36 Example b21multipleModels .. GENERATED FROM PYTHON SOURCE LINES 27-37 Creation of the object capturing the assisted specification algorithm. Its constructor takes three arguments: - the biogeme object containing the specifications and the database, - an object defining the objectives to minimize. Here, we use the opposite of the log lieklihood and the number of estimated parameters. - the name of the file where the estimated are saved, and organized into a Pareto set. .. GENERATED FROM PYTHON SOURCE LINES 37-43 .. code-block:: default assisted_specification = AssistedSpecification( biogeme_object=the_biogeme, multi_objectives=loglikelihood_dimension, pareto_file_name=PARETO_FILE_NAME, ) .. rst-class:: sphx-glr-script-out .. code-block:: none Unable to read file b21multiple_models.pareto. Pareto set empty. .. GENERATED FROM PYTHON SOURCE LINES 44-45 The algorithm is run. .. GENERATED FROM PYTHON SOURCE LINES 45-47 .. code-block:: default non_dominated_models = assisted_specification.run() .. rst-class:: sphx-glr-script-out .. code-block:: none File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_TRAIN B_COST B_TIME Function Relgrad Radius Rho 0 -0.49 -0.92 -0.88 -0.67 5.4e+03 0.041 10 1.1 ++ 1 -0.18 -0.73 -1 -1.2 5.3e+03 0.0072 1e+02 1.1 ++ 2 -0.16 -0.7 -1.1 -1.3 5.3e+03 0.00018 1e+03 1 ++ 3 -0.16 -0.7 -1.1 -1.3 5.3e+03 1.1e-07 1e+03 1 ++ default_specification=ASC:no_seg;B_COST:no_seg;TRAIN_TT:linear We consider all possible combinations of the catalogs. Model 0/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_TRAIN ASC_TRAIN_GA B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME Function Relgrad Radius Rho 0 -0.27 -0.11 -0.78 0.18 -0.34 -0.14 -0.13 -0.042 -0.021 -1 5.4e+03 0.036 10 1 ++ 1 -0.072 -0.068 -0.98 2.4 -1.5 0.65 0.41 -0.066 0.77 -1.6 5e+03 0.028 1e+02 0.94 ++ 2 -0.07 -0.2 -1.1 2.1 -1.6 0.66 0.28 -0.76 0.78 -1.7 5e+03 0.00071 1e+03 1 ++ 3 -0.07 -0.2 -1.1 2.1 -1.6 0.66 0.28 -0.76 0.78 -1.7 5e+03 5.1e-06 1e+03 1 ++ Model 1/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_male ASC_TRAIN ASC_TRAIN_male B_COST B_COST_GA B_TIME Function Relgrad Radius Rho 0 -0.32 -0.12 -0.37 -0.59 -0.89 -0.15 -1 5.3e+03 0.036 10 1 ++ 1 -0.17 0.22 0.41 -1.3 -0.94 -0.88 -1.7 5.2e+03 0.0094 1e+02 1 ++ 2 -0.18 0.25 0.42 -1.3 -0.96 -1 -1.7 5.2e+03 0.00022 1e+03 1 ++ 3 -0.18 0.25 0.42 -1.3 -0.96 -1 -1.7 5.2e+03 2.3e-07 1e+03 1 ++ Model 2/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_male ASC_TRAIN ASC_TRAIN_male B_COST B_TIME Function Relgrad Radius Rho 0 -0.52 -0.039 -0.33 -0.81 -0.89 -0.63 5.3e+03 0.043 10 1.1 ++ 1 -0.47 0.28 0.038 -1.2 -1 -1.2 5.2e+03 0.0093 1e+02 1.1 ++ 2 -0.46 0.31 0.089 -1.2 -1.1 -1.2 5.2e+03 0.00033 1e+03 1 ++ 3 -0.46 0.31 0.089 -1.2 -1.1 -1.2 5.2e+03 4.1e-07 1e+03 1 ++ Model 3/36 Model 4/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_TRAIN B_COST B_COST_GA B_TIME Function Relgrad Radius Rho 0 -0.5 -0.92 -0.9 0.097 -0.67 5.4e+03 0.041 10 1.1 ++ 1 -0.13 -0.71 -0.98 -0.74 -1.2 5.3e+03 0.0075 1e+02 1.1 ++ 2 -0.097 -0.68 -1 -1 -1.3 5.3e+03 0.0002 1e+03 1 ++ 3 -0.097 -0.68 -1 -1 -1.3 5.3e+03 1.2e-06 1e+03 1 ++ Model 5/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_TRAIN ASC_TRAIN_GA B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME Function Relgrad Radius Rho 0 -0.41 -0.23 -1 0.85 -0.75 -0.21 -0.31 -0.11 -0.052 -0.7 5.2e+03 0.049 10 1.1 ++ 1 -0.28 -0.19 -1.2 1.9 -1.5 0.54 0.19 -0.54 0.71 -1.1 5e+03 0.012 1e+02 1.1 ++ 2 -0.26 -0.21 -1.3 2 -1.6 0.59 0.23 -0.78 0.78 -1.2 5e+03 0.0006 1e+03 1 ++ 3 -0.26 -0.21 -1.3 2 -1.6 0.59 0.23 -0.78 0.78 -1.2 5e+03 1.8e-06 1e+03 1 ++ Model 6/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_TIME Function Relgrad Radius Rho 0 -0.46 -0.21 -0.15 -0.51 1 -0.8 -0.88 -0.6 5.1e+03 0.045 10 1.1 ++ 1 -0.6 -0.37 0.36 -0.54 1.7 -0.96 -1.1 -1.1 5e+03 0.012 1e+02 1.1 ++ 2 -0.61 -0.41 0.41 -0.53 1.9 -1.1 -1.1 -1.2 4.9e+03 0.0007 1e+03 1 ++ 3 -0.61 -0.41 0.41 -0.53 1.9 -1.1 -1.1 -1.2 4.9e+03 4.3e-06 1e+03 1 ++ Model 7/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_TRAIN B_COST B_TIME Function Relgrad Radius Rho 0 -0.3 -0.74 -0.39 -1 5.5e+03 0.044 10 1 ++ 1 -0.0041 -0.54 -0.93 -1.6 5.3e+03 0.0052 1e+02 1.1 ++ 2 0.0019 -0.51 -1 -1.7 5.3e+03 0.00015 1e+03 1 ++ 3 0.0019 -0.51 -1 -1.7 5.3e+03 1.4e-07 1e+03 1 ++ Model 8/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_TRAIN ASC_TRAIN_GA B_COST B_COST_GA B_TIME lambda_time Function Relgrad Radius Rho 0 -0.45 -0.2 -0.73 0.39 -0.73 -0.15 -1 1.6 5.5e+03 0.12 1 0.83 + 1 -0.19 -0.33 -1.1 1.4 -1.1 -0.2 -1.3 0.91 5.1e+03 0.022 10 1.1 ++ 2 0.034 -1.1 -0.87 2 -1.1 1.3 -1.9 0.26 5e+03 0.013 10 0.81 + 3 -0.066 -0.95 -1 2 -1.1 1 -1.7 0.36 5e+03 0.0012 1e+02 1 ++ 4 -0.068 -0.89 -1 2 -1.1 0.92 -1.7 0.38 5e+03 3.3e-05 1e+03 1 ++ 5 -0.068 -0.89 -1 2 -1.1 0.92 -1.7 0.38 5e+03 8.2e-08 1e+03 1 ++ Model 9/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_TRAIN B_COST B_TIME lambda_time Function Relgrad Radius Rho 0 -0.5 -0.71 -0.82 -1 1.7 5.6e+03 0.15 1 0.77 + 1 -0.35 -0.77 -1.3 -1.7 0.69 5.4e+03 0.049 10 1 ++ 2 0.017 -0.47 -1 -1.7 0.53 5.3e+03 0.002 1e+02 0.96 ++ 3 -0.0043 -0.48 -1.1 -1.7 0.51 5.3e+03 1.3e-05 1e+03 1 ++ 4 -0.0043 -0.48 -1.1 -1.7 0.51 5.3e+03 1.8e-09 1e+03 1 ++ Model 10/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME Function Relgrad Radius Rho 0 -0.47 -0.21 -0.15 -0.51 1 -0.82 -0.69 -0.15 -0.32 -0.094 -0.041 -0.59 5.1e+03 0.045 10 1.1 ++ 1 -0.62 -0.29 0.38 -0.57 1.8 -0.94 -1.4 0.51 0.15 -0.37 0.71 -1.1 4.9e+03 0.012 1e+02 1.1 ++ 2 -0.65 -0.33 0.44 -0.58 1.9 -1.1 -1.5 0.55 0.16 -0.6 0.75 -1.2 4.9e+03 0.00074 1e+03 1 ++ 3 -0.65 -0.33 0.44 -0.58 1.9 -1.1 -1.5 0.55 0.16 -0.6 0.75 -1.2 4.9e+03 5.9e-06 1e+03 1 ++ Model 11/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_COST_GA B_TIME Function Relgrad Radius Rho 0 -0.46 -0.19 -0.15 -0.51 1 -0.8 -0.88 -0.0059 -0.6 5.1e+03 0.045 10 1.1 ++ 1 -0.61 -0.93 0.36 -0.54 1.7 -0.97 -1.1 0.93 -1.1 4.9e+03 0.012 1e+02 1.1 ++ 2 -0.62 -0.98 0.41 -0.54 1.9 -1.1 -1.1 0.89 -1.2 4.9e+03 0.0007 1e+03 1 ++ 3 -0.62 -0.98 0.41 -0.54 1.9 -1.1 -1.1 0.89 -1.2 4.9e+03 4.4e-06 1e+03 1 ++ Model 12/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_male ASC_TRAIN ASC_TRAIN_male B_COST B_COST_GA B_TIME Function Relgrad Radius Rho 0 -0.52 -0.04 -0.33 -0.81 -0.91 0.11 -0.63 5.3e+03 0.043 10 1.1 ++ 1 -0.42 0.29 0.052 -1.1 -0.98 -0.72 -1.2 5.2e+03 0.0097 1e+02 1.1 ++ 2 -0.41 0.31 0.11 -1.2 -1 -1 -1.3 5.2e+03 0.00036 1e+03 1 ++ 3 -0.41 0.31 0.11 -1.2 -1 -1 -1.3 5.2e+03 9.1e-07 1e+03 1 ++ Model 13/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_male ASC_TRAIN ASC_TRAIN_male B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME Function Relgrad Radius Rho 0 -0.56 0.012 -0.36 -0.78 -1 0.16 -0.03 0.12 0.29 -0.63 5.3e+03 0.043 10 1.1 ++ 1 -0.48 0.3 0.017 -1.1 -1.4 0.49 0.17 -0.28 0.72 -1.2 5.2e+03 0.0097 1e+02 1.1 ++ 2 -0.47 0.33 0.069 -1.2 -1.5 0.53 0.18 -0.41 0.78 -1.3 5.2e+03 0.00037 1e+03 1 ++ 3 -0.47 0.33 0.069 -1.2 -1.5 0.53 0.18 -0.41 0.78 -1.3 5.2e+03 5.1e-07 1e+03 1 ++ Model 14/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_TRAIN B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME lambda_time Function Relgrad Radius Rho 0 -0.48 -0.72 -0.74 -0.31 -0.26 -0.092 -0.047 -1 1.6 5.6e+03 0.13 1 0.81 + 1 -0.22 -0.64 -0.91 0.12 -0.47 -0.36 -0.013 -1.6 0.65 5.3e+03 0.038 10 1 ++ 2 0.012 -0.49 -1.5 0.6 0.27 -0.59 0.8 -1.7 0.51 5.3e+03 0.00074 1e+02 1 ++ 3 0.0042 -0.49 -1.6 0.62 0.28 -0.65 0.81 -1.7 0.5 5.3e+03 7e-06 1e+03 1 ++ 4 0.0042 -0.49 -1.6 0.62 0.28 -0.65 0.81 -1.7 0.5 5.3e+03 1.3e-09 1e+03 1 ++ Model 15/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME Function Relgrad Radius Rho 0 -0.34 -0.18 -0.16 -0.44 0.47 -0.6 -0.69 -0.28 -0.25 -0.075 -0.042 -1 5.2e+03 0.036 10 1 ++ 1 -0.37 -0.29 0.34 -0.24 2 -0.98 -1.5 0.6 0.22 -0.3 0.76 -1.6 4.9e+03 0.018 1e+02 1 ++ 2 -0.43 -0.34 0.41 -0.25 2 -1.1 -1.5 0.63 0.21 -0.59 0.78 -1.7 4.9e+03 0.0011 1e+03 1 ++ 3 -0.43 -0.34 0.42 -0.25 2.1 -1.2 -1.6 0.63 0.21 -0.61 0.78 -1.7 4.9e+03 9.2e-06 1e+04 1 ++ 4 -0.43 -0.34 0.42 -0.25 2.1 -1.2 -1.6 0.63 0.21 -0.61 0.78 -1.7 4.9e+03 9.6e-08 1e+04 1 ++ Model 16/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_TIME lambda_time Function Relgrad Radius Rho 0 -0.45 -0.24 -0.25 -0.46 0.57 -0.64 -1 -0.92 1.9 5.5e+03 0.22 1 0.73 + 1 -0.47 -0.36 0.12 -0.56 1.6 -1.1 -0.95 -1 1.2 5e+03 0.044 10 1.2 ++ 2 -0.47 -0.36 0.12 -0.56 1.6 -1.1 -0.95 -1 1.2 5e+03 0.044 1.6 -11 - 3 -0.47 -0.36 0.12 -0.56 1.6 -1.1 -0.95 -1 1.2 5e+03 0.044 0.8 -0.46 - 4 -0.48 -0.4 0.3 -0.55 1.9 -1.2 -1.1 -1.5 0.42 4.9e+03 0.017 8 0.99 ++ 5 -0.42 -0.45 0.41 -0.21 1.9 -1.1 -1.1 -1.7 0.33 4.9e+03 0.00079 80 0.98 ++ 6 -0.42 -0.45 0.41 -0.21 1.9 -1.1 -1.1 -1.7 0.33 4.9e+03 3.4e-06 80 1 ++ Model 17/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_COST_GA B_TIME lambda_time Function Relgrad Radius Rho 0 -0.44 -0.24 -0.24 -0.46 0.57 -0.65 -1 -0.17 -0.92 1.9 5.5e+03 0.22 1 0.73 + 1 -0.47 -0.33 0.13 -0.55 1.6 -1.1 -0.94 -0.19 -1 1.2 5e+03 0.046 10 1.2 ++ 2 -0.47 -0.33 0.13 -0.55 1.6 -1.1 -0.94 -0.19 -1 1.2 5e+03 0.046 1.8 -14 - 3 -0.47 -0.33 0.13 -0.55 1.6 -1.1 -0.94 -0.19 -1 1.2 5e+03 0.046 0.88 -0.88 - 4 -0.46 -0.35 0.34 -0.56 1.9 -1.2 -1.2 -0.16 -1.6 0.36 4.9e+03 0.023 8.8 0.91 ++ 5 -0.43 -1.3 0.41 -0.21 1.9 -1.1 -1.1 1.6 -1.7 0.34 4.9e+03 0.0036 8.8 0.82 + 6 -0.42 -1.2 0.41 -0.22 2 -1.2 -1.1 1.2 -1.7 0.33 4.9e+03 0.00065 88 1.2 ++ 7 -0.42 -1.1 0.41 -0.22 2 -1.2 -1.1 0.98 -1.7 0.33 4.9e+03 0.00011 8.8e+02 1.1 ++ 8 -0.42 -1.1 0.41 -0.22 2 -1.2 -1.1 0.98 -1.7 0.33 4.9e+03 5.3e-06 8.8e+02 1 ++ Model 18/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_male ASC_TRAIN ASC_TRAIN_male B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME lambda_time Function Relgrad Radius Rho 0 -0.43 -0.22 -0.44 -0.66 -1 -0.42 -0.35 -0.11 -0.06 -0.9 2 5.7e+03 0.27 1 0.68 + 1 -0.52 0.77 0.56 -1.4 -0.96 0.3 -0.49 -0.51 0.066 -1.6 1.1 5.3e+03 0.049 1 0.84 + 2 -0.14 0.38 0.66 -1.2 -1.6 0.62 0.25 -0.36 0.96 -2.2 0.34 5.1e+03 0.029 1 0.87 + 3 -0.3 0.32 0.33 -1.3 -1.5 0.59 0.23 -0.37 0.84 -1.7 0.42 5.1e+03 0.0026 10 0.96 ++ 4 -0.3 0.32 0.35 -1.3 -1.6 0.59 0.23 -0.37 0.85 -1.7 0.45 5.1e+03 7.5e-05 1e+02 0.98 ++ 5 -0.3 0.32 0.35 -1.3 -1.6 0.59 0.23 -0.37 0.85 -1.7 0.45 5.1e+03 9.2e-08 1e+02 1 ++ Model 19/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_male ASC_TRAIN ASC_TRAIN_male B_COST B_TIME lambda_time Function Relgrad Radius Rho 0 -0.45 -0.24 -0.43 -0.62 -1 -0.89 1.8 5.6e+03 0.2 1 0.72 + 1 -0.65 0.58 0.39 -1.5 -1 -1.6 0.85 5.2e+03 0.028 10 0.94 ++ 2 -0.21 0.3 0.48 -1.3 -1.1 -1.9 0.42 5.1e+03 0.0096 1e+02 0.95 ++ 3 -0.29 0.3 0.36 -1.3 -1.1 -1.7 0.45 5.1e+03 0.0004 1e+03 0.98 ++ 4 -0.29 0.3 0.36 -1.3 -1.1 -1.7 0.45 5.1e+03 6.7e-07 1e+03 1 ++ Model 20/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_male ASC_TRAIN ASC_TRAIN_male B_COST B_COST_GA B_TIME lambda_time Function Relgrad Radius Rho 0 -0.44 -0.23 -0.43 -0.62 -1 -0.18 -0.89 1.9 5.6e+03 0.2 1 0.72 + 1 -0.63 0.58 0.39 -1.5 -0.97 -0.42 -1.6 0.86 5.2e+03 0.029 10 0.94 ++ 2 -0.14 0.3 0.51 -1.3 -1 -1 -1.9 0.4 5.1e+03 0.011 1e+02 0.93 ++ 3 -0.23 0.31 0.39 -1.3 -1 -1.1 -1.7 0.44 5.1e+03 0.00049 1e+03 0.98 ++ 4 -0.23 0.31 0.39 -1.3 -1 -1.1 -1.7 0.44 5.1e+03 1.9e-06 1e+03 1 ++ Model 21/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_TRAIN B_COST B_COST_GA B_TIME lambda_time Function Relgrad Radius Rho 0 -0.5 -0.71 -0.82 -0.17 -1 1.7 5.6e+03 0.15 1 0.77 + 1 -0.33 -0.78 -1.3 -0.38 -1.6 0.69 5.4e+03 0.049 10 1 ++ 2 0.085 -0.44 -0.96 -1.2 -1.7 0.53 5.3e+03 0.002 1e+02 0.96 ++ 3 0.06 -0.46 -1 -1.1 -1.7 0.51 5.3e+03 1e-05 1e+03 1 ++ 4 0.06 -0.46 -1 -1.1 -1.7 0.51 5.3e+03 7.2e-10 1e+03 1 ++ Model 22/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_TRAIN ASC_TRAIN_GA B_COST B_TIME Function Relgrad Radius Rho 0 -0.27 -0.12 -0.76 0.19 -0.37 -1 5.4e+03 0.044 10 1 ++ 1 -0.072 -0.11 -0.97 2.4 -0.96 -1.6 5e+03 0.027 1e+02 0.94 ++ 2 -0.067 -0.29 -1 2.1 -1.1 -1.7 5e+03 0.00066 1e+03 1 ++ 3 -0.067 -0.29 -1 2.1 -1.1 -1.7 5e+03 2.1e-06 1e+03 1 ++ Model 23/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_male ASC_TRAIN ASC_TRAIN_male B_COST B_TIME Function Relgrad Radius Rho 0 -0.33 -0.13 -0.37 -0.59 -0.89 -1 5.3e+03 0.036 10 1 ++ 1 -0.22 0.22 0.4 -1.3 -1 -1.6 5.2e+03 0.0091 1e+02 1 ++ 2 -0.24 0.25 0.4 -1.3 -1 -1.7 5.2e+03 0.00022 1e+03 1 ++ 3 -0.24 0.25 0.4 -1.3 -1 -1.7 5.2e+03 2.4e-07 1e+03 1 ++ Model 24/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_TRAIN B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME Function Relgrad Radius Rho 0 -0.29 -0.75 -0.36 -0.14 -0.13 -0.045 -0.023 -1 5.5e+03 0.035 10 1 ++ 1 0.0049 -0.54 -1.4 0.6 0.37 -0.17 0.73 -1.6 5.3e+03 0.0064 1e+02 1.1 ++ 2 0.011 -0.51 -1.5 0.63 0.28 -0.64 0.75 -1.7 5.3e+03 0.00037 1e+03 1 ++ 3 0.011 -0.51 -1.5 0.63 0.28 -0.64 0.75 -1.7 5.3e+03 2.2e-06 1e+03 1 ++ Model 25/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_male ASC_TRAIN ASC_TRAIN_male B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME Function Relgrad Radius Rho 0 -0.32 -0.13 -0.37 -0.6 -0.72 -0.28 -0.27 -0.082 -0.045 -1 5.3e+03 0.036 10 1 ++ 1 -0.22 0.24 0.38 -1.3 -1.4 0.56 0.22 -0.22 0.76 -1.6 5.2e+03 0.0092 1e+02 1 ++ 2 -0.25 0.27 0.38 -1.3 -1.5 0.6 0.23 -0.36 0.81 -1.7 5.2e+03 0.00022 1e+03 1 ++ 3 -0.25 0.27 0.38 -1.3 -1.5 0.6 0.23 -0.36 0.81 -1.7 5.2e+03 2.4e-07 1e+03 1 ++ Model 26/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_TRAIN ASC_TRAIN_GA B_COST B_COST_GA B_TIME Function Relgrad Radius Rho 0 -0.27 -0.12 -0.76 0.19 -0.36 -0.089 -1 5.4e+03 0.044 10 1 ++ 1 -0.08 -0.61 -0.98 2.4 -0.98 0.71 -1.6 5e+03 0.027 1e+02 0.93 ++ 2 -0.071 -0.87 -1.1 2.1 -1.1 0.92 -1.7 5e+03 0.00067 1e+03 1 ++ 3 -0.071 -0.87 -1.1 2.1 -1.1 0.92 -1.7 5e+03 2e-06 1e+03 1 ++ Model 27/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_TRAIN B_COST B_COST_GA B_TIME Function Relgrad Radius Rho 0 -0.3 -0.74 -0.39 -0.095 -1 5.5e+03 0.043 10 1 ++ 1 0.037 -0.52 -0.88 -0.53 -1.6 5.3e+03 0.0053 1e+02 1.1 ++ 2 0.061 -0.48 -0.95 -0.97 -1.7 5.3e+03 0.00033 1e+03 1.1 ++ 3 0.063 -0.48 -0.95 -1.1 -1.7 5.3e+03 1.1e-05 1e+04 1 ++ 4 0.063 -0.48 -0.95 -1.1 -1.7 5.3e+03 1.7e-08 1e+04 1 ++ Model 28/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_TRAIN B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME Function Relgrad Radius Rho 0 -0.49 -0.92 -1 0.2 -0.0026 0.026 0.21 -0.66 5.4e+03 0.041 10 1.1 ++ 1 -0.17 -0.74 -1.4 0.52 0.22 -0.53 0.69 -1.2 5.3e+03 0.0075 1e+02 1.1 ++ 2 -0.15 -0.71 -1.5 0.56 0.24 -0.66 0.75 -1.3 5.3e+03 0.0002 1e+03 1 ++ 3 -0.15 -0.71 -1.5 0.56 0.24 -0.66 0.75 -1.3 5.3e+03 1.5e-07 1e+03 1 ++ Model 29/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_COST_GA B_TIME Function Relgrad Radius Rho 0 -0.34 -0.18 -0.16 -0.43 0.47 -0.59 -0.76 -0.12 -1 5.2e+03 0.042 10 1 ++ 1 -0.36 -0.91 0.33 -0.21 2 -1 -1 0.89 -1.6 4.9e+03 0.018 1e+02 1 ++ 2 -0.39 -0.99 0.37 -0.2 2 -1.2 -1.1 0.91 -1.7 4.9e+03 0.0011 1e+03 1 ++ 3 -0.39 -0.99 0.38 -0.2 2 -1.2 -1.1 0.91 -1.7 4.9e+03 8.4e-06 1e+04 1 ++ 4 -0.39 -0.99 0.38 -0.2 2 -1.2 -1.1 0.91 -1.7 4.9e+03 5.4e-10 1e+04 1 ++ Model 30/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME lambda_time Function Relgrad Radius Rho 0 -0.43 -0.25 -0.22 -0.48 0.63 -0.69 -1 -0.42 -0.35 -0.11 -0.06 -0.93 2 5.6e+03 0.29 1 0.69 + 1 -0.35 -0.33 0.26 -0.46 1.6 -1.1 -0.7 0.05 -0.38 -0.23 -0.0044 -0.92 1.5 5.1e+03 0.079 10 1.1 ++ 2 -0.35 -0.33 0.26 -0.46 1.6 -1.1 -0.7 0.05 -0.38 -0.23 -0.0044 -0.92 1.5 5.1e+03 0.079 5 -1.4e+03 - 3 -0.35 -0.33 0.26 -0.46 1.6 -1.1 -0.7 0.05 -0.38 -0.23 -0.0044 -0.92 1.5 5.1e+03 0.079 2.5 -23 - 4 -0.35 -0.33 0.26 -0.46 1.6 -1.1 -0.7 0.05 -0.38 -0.23 -0.0044 -0.92 1.5 5.1e+03 0.079 1.2 -1.8 - 5 -0.44 -0.41 0.53 -0.31 2.1 -0.96 -1.3 -0.14 -0.44 -0.44 0.074 -2 0.26 4.9e+03 0.022 1.2 0.69 + 6 -0.45 -0.36 0.44 -0.26 2 -1.1 -1.5 0.66 0.23 -0.58 0.89 -1.7 0.31 4.9e+03 0.0046 12 0.91 ++ 7 -0.45 -0.37 0.45 -0.26 2 -1.1 -1.6 0.63 0.22 -0.59 0.82 -1.7 0.33 4.9e+03 9.7e-05 1.2e+02 1 ++ 8 -0.45 -0.37 0.45 -0.26 2 -1.1 -1.6 0.63 0.22 -0.59 0.82 -1.7 0.33 4.9e+03 1.4e-06 1.2e+02 1 ++ Model 31/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_TRAIN ASC_TRAIN_GA B_COST B_TIME lambda_time Function Relgrad Radius Rho 0 -0.45 -0.21 -0.73 0.39 -0.73 -1 1.6 5.5e+03 0.12 1 0.83 + 1 -0.2 -0.35 -1.1 1.4 -1.1 -1.3 0.9 5.1e+03 0.022 10 1.1 ++ 2 0.037 -0.36 -0.87 2 -1.1 -1.9 0.26 5e+03 0.012 10 0.82 + 3 -0.061 -0.31 -1 2 -1.1 -1.7 0.36 5e+03 0.0012 1e+02 1 ++ 4 -0.064 -0.31 -1 2 -1.1 -1.7 0.38 5e+03 3.1e-05 1e+03 1 ++ 5 -0.064 -0.31 -1 2 -1.1 -1.7 0.38 5e+03 3.6e-09 1e+03 1 ++ Model 32/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_TRAIN ASC_TRAIN_GA B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME lambda_time Function Relgrad Radius Rho 0 -0.43 -0.19 -0.73 0.37 -0.67 -0.28 -0.23 -0.082 -0.042 -1 1.6 5.4e+03 0.1 1 0.86 + 1 -0.19 -0.32 -1.1 1.4 -0.84 -0.12 -0.37 -0.21 -0.031 -1.3 0.83 5.1e+03 0.023 10 1.1 ++ 2 0.0088 -0.24 -0.93 2.1 -1.6 0.63 0.26 -0.57 0.83 -1.9 0.28 5e+03 0.0077 1e+02 0.91 ++ 3 -0.065 -0.22 -1 2.1 -1.6 0.67 0.28 -0.78 0.84 -1.7 0.36 5e+03 0.00067 1e+03 1 ++ 4 -0.068 -0.22 -1 2.1 -1.6 0.66 0.28 -0.79 0.84 -1.7 0.37 5e+03 9.8e-06 1e+04 1 ++ 5 -0.068 -0.22 -1 2.1 -1.6 0.66 0.28 -0.79 0.84 -1.7 0.37 5e+03 4e-10 1e+04 1 ++ Model 33/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_TRAIN ASC_TRAIN_GA B_COST B_TIME Function Relgrad Radius Rho 0 -0.36 -0.25 -0.88 0.66 -1 -0.79 5.2e+03 0.047 10 1.1 ++ 1 -0.28 -0.28 -1.2 1.9 -1.1 -1.1 5.1e+03 0.014 1e+02 1.1 ++ 2 -0.25 -0.3 -1.3 2 -1.1 -1.2 5.1e+03 0.0007 1e+03 1 ++ 3 -0.25 -0.3 -1.3 2 -1.1 -1.2 5.1e+03 2.4e-06 1e+03 1 ++ Model 34/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_TIME Function Relgrad Radius Rho 0 -0.34 -0.18 -0.17 -0.44 0.47 -0.59 -0.76 -1 5.2e+03 0.044 10 1 ++ 1 -0.36 -0.35 0.33 -0.21 2 -1 -1 -1.6 4.9e+03 0.018 1e+02 1 ++ 2 -0.39 -0.42 0.37 -0.2 2 -1.2 -1.1 -1.7 4.9e+03 0.0011 1e+03 1 ++ 3 -0.39 -0.42 0.38 -0.2 2 -1.2 -1.1 -1.7 4.9e+03 8.5e-06 1e+04 1 ++ 4 -0.39 -0.42 0.38 -0.2 2 -1.2 -1.1 -1.7 4.9e+03 5.5e-10 1e+04 1 ++ Model 35/36 File biogeme.toml has been parsed. *** Estimate b21multiple_models_000000 Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_TRAIN ASC_TRAIN_GA B_COST B_COST_GA B_TIME Function Relgrad Radius Rho 0 -0.43 -0.22 -1 0.9 -0.93 -0.072 -0.7 5.2e+03 0.046 10 1.1 ++ 1 -0.28 -0.87 -1.2 1.9 -1.1 0.98 -1.1 5.1e+03 0.011 1e+02 1.1 ++ 2 -0.25 -0.87 -1.3 2 -1.1 0.89 -1.2 5e+03 0.00055 1e+03 1 ++ 3 -0.25 -0.87 -1.3 2 -1.1 0.89 -1.2 5e+03 1.5e-06 1e+03 1 ++ Pareto file has been updated: b21multiple_models.pareto Before the algorithm: 1 models, with 1 Pareto. After the algorithm: 36 models, with 8 Pareto. VNS algorithm completed. Postprocessing of the Pareto optimal solutions Pareto set initialized from file with 36 elements [8 Pareto] and 0 invalid elements. File biogeme.toml has been parsed. *** Initial values of the parameters are obtained from the file __b21multiple_models_000000.iter Parameter values restored from __b21multiple_models_000000.iter Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_TIME lambda_time Function Relgrad Radius Rho 0 -0.51 -0.7 0.47 -0.42 2.1 -1 -1 -1.6 0.3 4.9e+03 0.014 10 0.99 ++ 1 -0.42 -0.41 0.41 -0.22 2 -1.1 -1.1 -1.7 0.34 4.9e+03 0.00042 1e+02 0.99 ++ 2 -0.42 -0.41 0.41 -0.22 2 -1.1 -1.1 -1.7 0.34 4.9e+03 3.6e-06 1e+02 1 ++ Results saved in file b21multiple_models_000000.html Results saved in file b21multiple_models_000000.pickle File biogeme.toml has been parsed. *** Initial values of the parameters are obtained from the file __b21multiple_models_000001.iter Cannot read file __b21multiple_models_000001.iter. Statement is ignored. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_COST_inc-100+ B_COST_inc-50-1 B_COST_inc-unde B_COST_inc-unkn B_TIME lambda_time Function Relgrad Radius Rho 0 -0.51 -0.73 0.39 -0.68 2.1 -1 -0.88 -0.028 -0.43 -0.23 -0.012 -1.4 0.32 4.9e+03 0.013 10 0.99 ++ 1 -0.45 -0.33 0.44 -0.26 2 -1.1 -1.5 0.56 0.15 -0.52 0.76 -1.7 0.35 4.9e+03 0.0019 1e+02 1 ++ 2 -0.45 -0.37 0.45 -0.26 2 -1.1 -1.6 0.63 0.21 -0.59 0.82 -1.7 0.33 4.9e+03 4.1e-05 1e+03 1 ++ 3 -0.45 -0.37 0.45 -0.26 2 -1.1 -1.6 0.63 0.21 -0.59 0.82 -1.7 0.33 4.9e+03 4.6e-07 1e+03 1 ++ Results saved in file b21multiple_models_000001.html Results saved in file b21multiple_models_000001.pickle File biogeme.toml has been parsed. *** Initial values of the parameters are obtained from the file __b21multiple_models_000002.iter Cannot read file __b21multiple_models_000002.iter. Statement is ignored. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_TRAIN B_COST B_TIME Function Relgrad Radius Rho 0 -0.19 -0.62 -1.1 -1.2 5.3e+03 0.017 10 1.1 ++ 1 -0.16 -0.7 -1.1 -1.3 5.3e+03 0.00069 1e+02 1 ++ 2 -0.16 -0.7 -1.1 -1.3 5.3e+03 1.2e-06 1e+02 1 ++ Results saved in file b21multiple_models_000002.html Results saved in file b21multiple_models_000002.pickle File biogeme.toml has been parsed. *** Initial values of the parameters are obtained from the file __b21multiple_models_000003.iter Cannot read file __b21multiple_models_000003.iter. Statement is ignored. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_TRAIN ASC_TRAIN_GA B_COST B_TIME Function Relgrad Radius Rho 0 -0.22 -0.15 -0.48 1 -0.93 -1.7 5.2e+03 0.049 10 1.1 ++ 1 -0.06 -0.28 -0.96 2.1 -1.1 -1.6 5e+03 0.013 1e+02 1 ++ 2 -0.065 -0.27 -1 2.1 -1.1 -1.7 5e+03 0.00034 1e+03 1 ++ 3 -0.065 -0.27 -1 2.1 -1.1 -1.7 5e+03 5.6e-07 1e+03 1 ++ Results saved in file b21multiple_models_000003.html Results saved in file b21multiple_models_000003.pickle File biogeme.toml has been parsed. *** Initial values of the parameters are obtained from the file __b21multiple_models_000004.iter Cannot read file __b21multiple_models_000004.iter. Statement is ignored. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_COST_GA B_TIME lambda_time Function Relgrad Radius Rho 0 -0.26 -0.88 0.16 -1.2 2 -0.33 -1 -0.015 -1.2 0.69 5e+03 0.024 10 0.94 ++ 1 -0.37 -1.4 0.39 -0.068 1.9 -1.3 -1.1 1.7 -1.7 0.2 4.9e+03 0.0075 10 0.82 + 2 -0.42 -1.2 0.42 -0.21 2 -1.2 -1.1 1.3 -1.7 0.33 4.9e+03 0.0012 1e+02 1.1 ++ 3 -0.42 -1.1 0.41 -0.22 2 -1.2 -1.1 1 -1.7 0.33 4.9e+03 0.00022 1e+03 1.1 ++ 4 -0.42 -1 0.41 -0.22 2 -1.2 -1.1 0.92 -1.7 0.33 4.9e+03 1.6e-05 1e+04 1 ++ 5 -0.42 -1 0.41 -0.22 2 -1.2 -1.1 0.92 -1.7 0.33 4.9e+03 9e-08 1e+04 1 ++ Results saved in file b21multiple_models_000004.html Results saved in file b21multiple_models_000004.pickle File biogeme.toml has been parsed. *** Initial values of the parameters are obtained from the file __b21multiple_models_000005.iter Cannot read file __b21multiple_models_000005.iter. Statement is ignored. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_TRAIN B_COST B_TIME lambda_time Function Relgrad Radius Rho 0 -0.053 -0.42 -1.1 -1.6 0.4 5.3e+03 0.018 10 1 ++ 1 -0.00093 -0.47 -1.1 -1.7 0.52 5.3e+03 0.0011 1e+02 0.98 ++ 2 -0.0046 -0.48 -1.1 -1.7 0.51 5.3e+03 1.6e-05 1e+03 1 ++ 3 -0.0046 -0.48 -1.1 -1.7 0.51 5.3e+03 2.8e-09 1e+03 1 ++ Results saved in file b21multiple_models_000005.html Results saved in file b21multiple_models_000005.pickle File biogeme.toml has been parsed. *** Initial values of the parameters are obtained from the file __b21multiple_models_000006.iter Cannot read file __b21multiple_models_000006.iter. Statement is ignored. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_TRAIN ASC_TRAIN_GA B_COST B_TIME lambda_time Function Relgrad Radius Rho 0 -0.14 -0.19 -0.75 1 -1 -1.5 0.28 5.1e+03 0.025 10 1.1 ++ 1 -0.063 -0.3 -0.97 2 -1.1 -1.7 0.42 5e+03 0.0067 1e+02 0.99 ++ 2 -0.063 -0.31 -1 2 -1.1 -1.7 0.38 5e+03 8.5e-05 1e+03 1 ++ 3 -0.063 -0.31 -1 2 -1.1 -1.7 0.38 5e+03 6.6e-08 1e+03 1 ++ Results saved in file b21multiple_models_000006.html Results saved in file b21multiple_models_000006.pickle File biogeme.toml has been parsed. *** Initial values of the parameters are obtained from the file __b21multiple_models_000007.iter Cannot read file __b21multiple_models_000007.iter. Statement is ignored. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. ASC_CAR ASC_CAR_GA ASC_CAR_male ASC_TRAIN ASC_TRAIN_GA ASC_TRAIN_male B_COST B_TIME Function Relgrad Radius Rho 0 -0.45 -0.71 0.42 -0.47 2.3 -1 -0.9 -1.5 4.9e+03 0.024 10 1 ++ 1 -0.39 -0.39 0.38 -0.2 2 -1.2 -1.1 -1.7 4.9e+03 0.0011 1e+02 1 ++ 2 -0.39 -0.39 0.38 -0.2 2 -1.2 -1.1 -1.7 4.9e+03 3e-06 1e+02 1 ++ Results saved in file b21multiple_models_000007.html Results saved in file b21multiple_models_000007.pickle Pareto: 8 Condidered: 36 Removed: 10 .. GENERATED FROM PYTHON SOURCE LINES 48-53 .. code-block:: default summary, description = compile_estimation_results( non_dominated_models, use_short_names=True ) print(summary) .. rst-class:: sphx-glr-script-out .. code-block:: none Model_000000 Model_000001 Model_000002 Model_000003 Model_000004 Model_000005 Model_000006 Model_000007 Number of estimated parameters 9 13 4 6 10 5 7 8 Sample size 6768 6768 6768 6768 6768 6768 6768 6768 Final log likelihood -4881.916954 -4862.364941 -5331.252007 -5021.233909 -4879.461203 -5292.095411 -4995.755387 -4900.883369 Akaike Information Criterion 9781.833907 9750.729881 10670.504014 10054.467818 9778.922406 10594.190822 10005.510775 9817.766739 Bayesian Information Criterion 9843.213555 9839.389373 10697.783858 10095.387584 9847.122015 10628.290626 10053.250501 9872.326426 ASC_CAR (t-test) -0.417 (-4.23) -0.453 (-4.4) -0.155 (-2.66) -0.0646 (-1.25) -0.422 (-4.29) -0.00462 (-0.0963) -0.064 (-1.22) -0.389 (-3.95) ASC_CAR_GA (t-test) -0.447 (-2.19) -0.371 (-1.84) -0.268 (-1.35) -1.03 (-2.56) -0.313 (-1.59) -0.415 (-2.02) ASC_CAR_male (t-test) 0.412 (3.95) 0.449 (4.17) 0.413 (3.95) 0.377 (3.65) ASC_TRAIN (t-test) -0.219 (-2.42) -0.261 (-2.82) -0.701 (-8.49) -1.05 (-14.6) -0.22 (-2.44) -0.485 (-7.53) -1.03 (-13.9) -0.203 (-2.23) ASC_TRAIN_GA (t-test) 1.96 (21.1) 1.99 (21.1) 2.13 (24.3) 1.96 (21.2) 2.04 (22.8) 2.03 (22.4) ASC_TRAIN_male (t-test) -1.15 (-13.4) -1.12 (-12.9) -1.15 (-13.4) -1.2 (-14.1) B_COST (t-test) -1.09 (-15) -1.58 (-5.84) -1.08 (-15.9) -1.07 (-15) -1.1 (-15.1) -1.08 (-15.9) -1.1 (-14.8) -1.06 (-15.2) B_TIME (t-test) -1.69 (-21.2) -1.71 (-21.3) -1.28 (-12.3) -1.68 (-21.5) -1.7 (-21.3) -1.67 (-21.9) -1.67 (-21.3) -1.7 (-21.5) lambda_time (t-test) 0.334 (4.54) 0.329 (4.5) 0.334 (4.55) 0.51 (6.6) 0.382 (5.18) B_COST_inc-100+ (t-test) 0.629 (2.29) B_COST_inc-50-100 (t-test) 0.215 (0.69) B_COST_inc-under50 (t-test) -0.588 (-1.08) B_COST_inc-unknown (t-test) 0.817 (2.56) B_COST_GA (t-test) 0.915 (1.85) .. GENERATED FROM PYTHON SOURCE LINES 54-55 Explanation of the short names of the model. .. GENERATED FROM PYTHON SOURCE LINES 55-58 .. code-block:: default for k, v in description.items(): if k != v: print(f'{k}: {v} AIC={summary.at["Akaike Information Criterion", k]}') .. rst-class:: sphx-glr-script-out .. code-block:: none Model_000000: ASC:MALE-GA;B_COST:no_seg;TRAIN_TT:boxcox AIC=9781.833907090044 Model_000001: ASC:MALE-GA;B_COST:INCOME;TRAIN_TT:boxcox AIC=9750.72988109646 Model_000002: ASC:no_seg;B_COST:no_seg;TRAIN_TT:linear AIC=10670.504013896403 Model_000003: ASC:GA;B_COST:no_seg;TRAIN_TT:log AIC=10054.467818331683 Model_000004: ASC:MALE-GA;B_COST:GA;TRAIN_TT:boxcox AIC=9778.922405513185 Model_000005: ASC:no_seg;B_COST:no_seg;TRAIN_TT:boxcox AIC=10594.19082155567 Model_000006: ASC:GA;B_COST:no_seg;TRAIN_TT:boxcox AIC=10005.510774519298 Model_000007: ASC:MALE-GA;B_COST:no_seg;TRAIN_TT:log AIC=9817.76673883066 .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 12.576 seconds) .. _sphx_glr_download_auto_examples_swissmetro_plot_b21multiple_models.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_b21multiple_models.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_b21multiple_models.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_