# Gallery of examples

## Assisted specification with Biogeme

Examples discussed in Bierlaire and Ortelli (2023) Assisted Specification with Biogeme 3.2.12

Combination of many specifications

Investigation of several choice models

Catalog of nonlinear specifications

Catalog for alternative specific coefficients

Catalog for segmented parameters

Segmentations and alternative specific specification

Combine many specifications: exception is raised

Combine many specifications: assisted specification algorithm

Data preparation for Swissmetro

## Calculating indicators with Biogeme

Examples discussed in Bierlaire (2018) Calculating indicators with PandasBiogeme

Examples of mathematical expressions

Estimation and simulation of a nested logit model

Calculation of willingness to pay

Specification of a nested logit model

## Choice models with one latent variable

You find here several examples of so called “hybrid choice models”, discussed in Bierlaire (2018) Estimating choice models with latent variables with PandasBiogeme

Measurement equations: continuous indicators

Measurement equations: discrete indicators

Choice model with a latent variable: sequential estimation

Choice model with a latent variable: sequential estimation (Monte-Carlo)

Choice model with a latent variable: maximum likelihood estimation

Choice model with a latent variable: maximum likelihood estimation (Monte-Carlo)

Illustration of a common estimation problem

Investigation of the estimation problem

## Choice models with another latent variable

You find here another example of a “hybrid choice models”.

Data processing for the optima case study

Measurement equations: discrete indicators

Choice model with latent variable: sequential estimation

Choice model with the latent variable: maximum likelihood estimation

## Monte-Carlo integration with Biogeme

Example discussed in Bierlaire (2019) Monte-Carlo integration with Biogeme

Specification of the mixtures of logit

Antithetic draws explicitly generated

Estimation of mixtures of logit

Mixtures of logit with Monte-Carlo 2000 draws

Mixtures of logit with Monte-Carlo 500 draws

Mixtures of logit with Monte-Carlo 2000 antithetic draws

Mixtures of logit with Monte-Carlo 500 antithetic draws

Mixtures of logit with Monte-Carlo 2000 Halton draws

Mixtures of logit with Monte-Carlo 500 Halton draws

Mixtures of logit with Monte-Carlo 2000 MLHS draws

Mixtures of logit with Monte-Carlo 500 MLHS draws

Mixtures of logit with Monte-Carlo 2000 antithetic MLHS draws

Mixtures of logit with Monte-Carlo 2000 antithetic MLHS draws

Data preparation for Swissmetro

Data preparation for Swissmetro: one observation

## Programming with Biogeme

Examples of the use of various Biogeme objects for programming.

## Sampling of alternatives

Examples discussed in Bierlaire and Paschalidis (2023) Estimating MEV models with samples of alternatives

## Biogeme examples for the Swissmetro data

You find here several examples of models that can be estimated and simulated with Biogeme.

Illustration of additional features of Biogeme

Nested logit model normalized from bottom

Nested logit model normalized from bottom

Cross-nested logit (old syntax)

Simulation of a cross-nested logit model

Mixture of logit with panel data

Mixture of logit with panel data

Nested logit with corrections for endogeneous sampling

Discrete mixture with panel data

Discrete mixture with panel data

Discrete mixture with panel data

Mixture with lognormal distribution

Mixture with lognormal distribution

Calculation of individual level parameters

Specification of a catalog of models

Re-estimate the Pareto optimal models

Specification of a catalog of models

Re-estimate the Pareto optimal models

Mixture of logit with Halton draws

Triangular mixture with panel data

Data preparation for Swissmetro (binary choice)

Data preparation for Swissmetro

Panel data preparation for Swissmetro