Choice Modeling

Modeling of choice behavior based on Random Utility Theory implemented using Python.

Models

• Multinomial Logit Model (MNL)
• Nested Logit Model (NL)
• TasteNet-MNL [Han+, 2020]

For Mixed Logit Model (MXL) and Latent Class Logit Model (LCCM), I recommend using the Python package xlogit or the R packages mlogit and flemix.

References

• Tetsuro Hyodo. "How to estimate discrete choice models with R" https://www2.kaiyodai.ac.jp/~hyodo/Logit_by_R.pdf
• Han, Yafei, Christopher Zegras, Francisco Camara Pereira, and Moshe Ben-Akiva. 2020. “A Neural-Embedded Choice Model: TasteNet-MNL Modeling Taste Heterogeneity with Flexibility and Interpretability.” arXiv [econ.EM]. arXiv. http://arxiv.org/abs/2002.00922.