IDEAS home Printed from https://ideas.repec.org/r/eee/transb/v106y2017icp76-101.html

Random taste heterogeneity in discrete choice models: Flexible nonparametric finite mixture distributions

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Dubey, Subodh & Bansal, Prateek & Daziano, Ricardo A. & Guerra, Erick, 2020. "A Generalized Continuous-Multinomial Response Model with a t-distributed Error Kernel," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 114-141.
  2. Ren, Xiyuan & Chow, Joseph Y.J. & Pandey, Venktesh & Yuan, Linfei, 2026. "Microtransit revenue management informed by citywide travel demand and joint subscription–mode choice modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 210(C).
  3. Melvin Wong & Bilal Farooq, 2019. "Information processing constraints in travel behaviour modelling: A generative learning approach," Papers 1907.07036, arXiv.org, revised Jul 2019.
  4. Krueger, Rico & Rashidi, Taha H. & Vij, Akshay, 2020. "A Dirichlet process mixture model of discrete choice: Comparisons and a case study on preferences for shared automated vehicles," Journal of choice modelling, Elsevier, vol. 36(C).
  5. Bhat, Chandra R. & Mondal, Aupal & Pinjari, Abdul Rawoof, 2025. "A flexible non-normal random coefficient multinomial probit model: Application to investigating commuter's mode choice behavior in a developing economy context," Transportation Research Part B: Methodological, Elsevier, vol. 195(C).
  6. Vanaja, Shiuli, 2021. "Are People Making Correct Choices? Drivers of Water Source Choices in Rural Jharkhand, India," 2021 Conference, August 17-31, 2021, Virtual 315156, International Association of Agricultural Economists.
  7. Tinessa, Fiore & Marzano, Vittorio & Papola, Andrea, 2020. "Mixing distributions of tastes with a Combination of Nested Logit (CoNL) kernel: Formulation and performance analysis," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 1-23.
  8. Youssef M Aboutaleb & Mazen Danaf & Yifei Xie & Moshe Ben-Akiva, 2020. "Sparse Covariance Estimation in Logit Mixture Models," Papers 2001.05034, arXiv.org.
  9. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
  10. Tabasi, Maliheh & Rose, John M. & Pellegrini, Andrea & Hossein Rashidi, Taha, 2024. "An empirical investigation of the distribution of travellers’ willingness-to-pay: A comparison between a parametric and nonparametric approach," Transport Policy, Elsevier, vol. 146(C), pages 312-321.
  11. Bansal, Prateek & Hurtubia, Ricardo & Tirachini, Alejandro & Daziano, Ricardo A., 2019. "Flexible estimates of heterogeneity in crowding valuation in the New York City subway," Journal of choice modelling, Elsevier, vol. 31(C), pages 124-140.
  12. John Buckell & Alice Wreford & Matthew Quaife & Thomas O. Hancock, 2025. "A Break from the Norm? Parametric Representations of Preference Heterogeneity for Discrete Choice Models in Health," Medical Decision Making, , vol. 45(8), pages 987-1001, November.
  13. Bansal, Prateek & Krueger, Rico & Bierlaire, Michel & Daziano, Ricardo A. & Rashidi, Taha H., 2020. "Bayesian estimation of mixed multinomial logit models: Advances and simulation-based evaluations," Transportation Research Part B: Methodological, Elsevier, vol. 131(C), pages 124-142.
  14. Beeramoole, Prithvi Bhat & Arteaga, Cristian & Pinz, Alban & Haque, Md Mazharul & Paz, Alexander, 2023. "Extensive hypothesis testing for estimation of mixed-Logit models," Journal of choice modelling, Elsevier, vol. 47(C).
  15. Li, Xiaodong & Feng, Tao & Rasouli, Soora & Jia, Peng & Kuang, Haibo, 2026. "Decomposing random taste heterogeneity in discrete choice modeling: A mixture density network-embedded logit model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 212(C).
  16. Rico Krueger & Taha H. Rashidi & Akshay Vij, 2019. "Semi-Parametric Hierarchical Bayes Estimates of New Yorkers' Willingness to Pay for Features of Shared Automated Vehicle Services," Papers 1907.09639, arXiv.org.
  17. Jourdain, Damien & Lairez, Juliette & Striffler, Bruno & Lundhede, Thomas, 2022. "A choice experiment approach to evaluate maize farmers’ decision-making processes in Lao PDR," Journal of choice modelling, Elsevier, vol. 44(C).
  18. Bansal, Prateek & Daziano, Ricardo A & Guerra, Erick, 2018. "Minorization-Maximization (MM) algorithms for semiparametric logit models: Bottlenecks, extensions, and comparisons," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 17-40.
  19. Danaf, Mazen & Atasoy, Bilge & Ben-Akiva, Moshe, 2020. "Logit mixture with inter and intra-consumer heterogeneity and flexible mixing distributions," Journal of choice modelling, Elsevier, vol. 35(C).
  20. Ke Wang & Chandra R. Bhat & Xin Ye, 2023. "A multinomial probit analysis of shanghai commute mode choice," Transportation, Springer, vol. 50(4), pages 1471-1495, August.
  21. Rico Krueger & Akshay Vij & Taha H. Rashidi, 2018. "A Dirichlet Process Mixture Model of Discrete Choice," Papers 1801.06296, arXiv.org.
  22. Hynes, S. & Ankamah-Yeboah, I. & O’Neill, S. & Needham, K. & Bich Xuan, B. & Armstrong, C., 2020. "Entropy balancing for causal effects in discrete choice analysis: The Blue Planet II effect," Working Papers 309500, National University of Ireland, Galway, Socio-Economic Marine Research Unit.
  23. S. Van Cranenburgh & S. Wang & A. Vij & F. Pereira & J. Walker, 2021. "Choice modelling in the age of machine learning -- discussion paper," Papers 2101.11948, arXiv.org, revised Nov 2021.
  24. Sfeir, Georges & Abou-Zeid, Maya & Rodrigues, Filipe & Pereira, Francisco Camara & Kaysi, Isam, 2021. "Latent class choice model with a flexible class membership component: A mixture model approach," Journal of choice modelling, Elsevier, vol. 41(C).
  25. Chen, Pengfang & Zhang, Xiaoqiang & Gao, Dongsheng, 2024. "Preference heterogeneity analysis on train choice behaviour of high-speed railway passengers: A case study in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 188(C).
  26. Subodh Dubey & Prateek Bansal & Ricardo A. Daziano & Erick Guerra, 2019. "A Generalized Continuous-Multinomial Response Model with a t-distributed Error Kernel," Papers 1904.08332, arXiv.org, revised Jan 2020.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.