BIOGEME

Biogeme is a open source Python package designed for the maximum likelihood estimation of parametric models in general, with a special emphasis on discrete choice models. It relies on the package Python Data Analysis Library called Pandas. Biogeme used to be a stand alone software package, written in C++. All the material related to the previous versions of Biogeme are available on the old webpage. (Source: http://plato.asu.edu)


References in zbMATH (referenced in 17 articles )

Showing results 1 to 17 of 17.
Sorted by year (citations)

  1. Bechler, Georg; Steinhardt, Claudius; Mackert, Jochen; Klein, Robert: Product line optimization in the presence of preferences for compromise alternatives (2021)
  2. Nguyen K. Huynh, Sergio Bejar, Vineeta Yadav, Bumba Mukherjee: IDCeMPy: Python Package for Inflated Discrete Choice Models (2021) not zbMATH
  3. Pérez-López, José-Benito; Novales, Margarita; Varela-García, Francisco-Alberto; Orro, Alfonso: Residential location econometric choice modeling with irregular zoning: common border spatial correlation metric (2020)
  4. Jalali, Hamed; Carmen, Raïsa; van Nieuwenhuyse, Inneke; Boute, Robert: Quality and pricing decisions in production/inventory systems (2019)
  5. de Grange, Louis; González, Felipe; Vargas, Ignacio; Troncoso, Rodrigo: A logit model with endogenous explanatory variables and network externalities (2015)
  6. Baur, Alexander; Klein, Robert; Steinhardt, Claudius: Model-based decision support for optimal brochure pricing: applying advanced analytics in the tour operating industry (2014)
  7. Hurtubia, Ricardo; Bierlaire, Michel: Estimation of bid functions for location choice and price modeling with a latent variable approach (2014)
  8. Fosgerau, Mogens; Mabit, Stefan L.: Easy and flexible mixture distributions (2013)
  9. Martinetti, Davide; Lucadamo, Antonio; Montes, Susana: How to introduce fuzzy rationality measures and fuzzy revealed preferences into a discrete choice model (2013)
  10. Chorus, Caspar G.: Random regret-based discrete choice modeling. A tutorial. (2012)
  11. Amador, Francisco Javier; Cherchi, Elisabetta: Econometric effects of utility order-preserving transformations in discrete choice models (2011)
  12. Rusmevichientong, Paat; Shen, Zuo-Jun Max; Shmoys, David B.: Dynamic assortment optimization with a multinomial logit choice model and capacity constraint (2010)
  13. Kristoffersson, Ida; Engelson, Leonid: A dynamic transportation model for the Stockholm area: Implementation issues regarding departure time choice and OD-pair reduction (2009)
  14. Natarajan, Karthik; Song, Miao; Teo, Chung-Piaw: Persistency model and its applications in choice modeling (2009)
  15. Chiou, Lesley; Walker, Joan L.: Masking identification of discrete choice models under simulation methods (2007)
  16. Antonini, Gianluca; Martinez, Santiago Venegas; Bierlaire, Michel; Thiran, Jean Philippe: Behavioral priors for detection and tracking of pedestrians in video sequences (2006) ioport
  17. Bierlaire, Michel: A theoretical analysis of the cross-nested logit model (2006)