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Normalization and correlation of cross-nested logit models

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Cited by:

  1. Cinzia Cirillo & Renting Xu & Fabian Bastin, 2016. "A Dynamic Formulation for Car Ownership Modeling," Transportation Science, INFORMS, vol. 50(1), pages 322-335, February.
  2. Newman, Jeffrey P. & Lurkin, Virginie & Garrow, Laurie A., 2018. "Computational methods for estimating multinomial, nested, and cross-nested logit models that account for semi-aggregate data," Journal of choice modelling, Elsevier, vol. 26(C), pages 28-40.
  3. Gu, Yu & Chen, Anthony & Kitthamkesorn, Songyot, 2026. "On the satisfaction function of random utility models: A theoretical review with new developments in weibit-based choice models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 205(C).
  4. Lemp, Jason D. & Kockelman, Kara M. & Damien, Paul, 2010. "The continuous cross-nested logit model: Formulation and application for departure time choice," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 646-661, June.
  5. Fiore Tinessa & Vittorio Marzano & Andrea Papola, 2021. "Choice probabilities and correlations in closed-form route choice models: specifications and drawbacks," Papers 2110.07224, arXiv.org.
  6. Robin, Th. & Antonini, G. & Bierlaire, M. & Cruz, J., 2009. "Specification, estimation and validation of a pedestrian walking behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 36-56, January.
  7. Anna Fernández-Antolín & Matthieu Lapparent & Michel Bierlaire, 2018. "Modeling purchases of new cars: an analysis of the 2014 French market," Theory and Decision, Springer, vol. 84(2), pages 277-303, March.
  8. 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.
  9. Tinessa, Fiore, 2021. "Closed-form random utility models with mixture distributions of random utilities: Exploring finite mixtures of qGEV models," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 262-288.
  10. Flügel, Stefan & Halse, Askill H. & Ortúzar, Juan de Dios & Rizzi, Luis I., 2015. "Methodological challenges in modelling the choice of mode for a new travel alternative using binary stated choice data – The case of high speed rail in Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 438-451.
  11. Julie Poirier, 2012. "How to Deal with Protest Bids and Preference for the Status Quo in Choice Experiments ?," Working Papers 2012-02, Center for Research in Economics and Statistics.
  12. Mai, Tien & Frejinger, Emma & Fosgerau, Mogens & Bastin, Fabian, 2017. "A dynamic programming approach for quickly estimating large network-based MEV models," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 179-197.
  13. Mai, Tien, 2016. "A method of integrating correlation structures for a generalized recursive route choice model," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 146-161.
  14. Astegiano, Paola & Akinc, Deniz & Himpe, Willem & Tampère, Chris M.J. & Vandebroek, Martina, 2017. "Quantifying the explanatory power of mobility-related attributes in explaining vehicle ownership decisions," Research in Transportation Economics, Elsevier, vol. 66(C), pages 2-11.
  15. Liu, Yan & Cirillo, Cinzia, 2018. "A generalized dynamic discrete choice model for green vehicle adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PB), pages 288-302.
  16. Marzano, Vittorio & Papola, Andrea, 2008. "On the covariance structure of the Cross-Nested Logit model," Transportation Research Part B: Methodological, Elsevier, vol. 42(2), pages 83-98, February.
  17. Marzano, Vittorio, 2014. "A simple procedure for the calculation of the covariances of any Generalized Extreme Value model," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 151-162.
  18. Newman, Jeffrey P., 2008. "Normalization of network generalized extreme value models," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 958-969, December.
  19. Alessandro Iaria, & Wang, Ao, 2021. "An Empirical Model of Quantity Discounts with Large Choice Sets," The Warwick Economics Research Paper Series (TWERPS) 1378, University of Warwick, Department of Economics.
  20. Papola, Andrea, 2016. "A new random utility model with flexible correlation pattern and closed-form covariance expression: The CoRUM," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 80-96.
  21. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2015. "Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model," Journal of choice modelling, Elsevier, vol. 16(C), pages 58-68.
  22. Gu, Yu & Chen, Anthony & Kitthamkesorn, Songyot, 2022. "Weibit choice models: Properties, mode choice application and graphical illustrations," Journal of choice modelling, Elsevier, vol. 44(C).
  23. Marzano, Vittorio & Papola, Andrea & Simonelli, Fulvio & Vitillo, Roberta, 2013. "A practically tractable expression of the covariances of the Cross-Nested Logit model," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 1-11.
  24. Drabas, Tomasz & Wu, Cheng-Lung, 2013. "Modelling air carrier choices with a Segment Specific Cross Nested Logit model," Journal of Air Transport Management, Elsevier, vol. 32(C), pages 8-16.
  25. Sener, Ipek N. & Pendyala, Ram M. & Bhat, Chandra R., 2011. "Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior," Journal of Transport Geography, Elsevier, vol. 19(2), pages 294-303.
  26. Perez-Lopez, Jose-Benito & Novales, Margarita & Orro, Alfonso, 2022. "Spatially correlated nested logit model for spatial location choice," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 1-12.
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