IDEAS home Printed from https://ideas.repec.org/r/eee/transb/v45y2011i7p923-939.html
   My bibliography  Save this item

The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models

Citations

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


Cited by:

  1. Vij, Akshay & Krueger, Rico, 2017. "Random taste heterogeneity in discrete choice models: Flexible nonparametric finite mixture distributions," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 76-101.
  2. Silveira Santos, Luís & Proença, Isabel, 2019. "The inversion of the spatial lag operator in binary choice models: Fast computation and a closed formula approximation," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 74-102.
  3. Jean-François Richard, 2015. "Likelihood Evaluation of High-Dimensional Spatial Latent Gaussian Models with Non-Gaussian Response Variables," Working Paper 5778, Department of Economics, University of Pittsburgh.
  4. Zhou, Yiwei & Wang, Xiaokun & Holguín-Veras, José, 2016. "Discrete choice with spatial correlation: A spatial autoregressive binary probit model with endogenous weight matrix (SARBP-EWM)," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 440-455.
  5. Bhat, Chandra R. & Astroza, Sebastian & Hamdi, Amin S., 2017. "A spatial generalized ordered-response model with skew normal kernel error terms with an application to bicycling frequency," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 126-148.
  6. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
  7. Keemin Sohn, 2017. "An Expectation-Maximization Algorithm to Estimate the Integrated Choice and Latent Variable Model," Transportation Science, INFORMS, vol. 51(3), pages 946-967, August.
  8. Astroza, Sebastian & Bhat, Prerna C. & Bhat, Chandra R. & Pendyala, Ram M. & Garikapati, Venu M., 2018. "Understanding activity engagement across weekdays and weekend days: A multivariate multiple discrete-continuous modeling approach," Journal of choice modelling, Elsevier, vol. 28(C), pages 56-70.
  9. Stephane Hess, 2014. "Latent class structures: taste heterogeneity and beyond," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 14, pages 311-330, Edward Elgar Publishing.
  10. Sabreena Anowar & Naveen Eluru & Luis F. Miranda-Moreno, 2014. "Alternative Modeling Approaches Used for Examining Automobile Ownership: A Comprehensive Review," Transport Reviews, Taylor & Francis Journals, vol. 34(4), pages 441-473, July.
  11. Leung, Kevin Y.K. & Astroza, Sebastian & Loo, Becky P.Y. & Bhat, Chandra R., 2019. "An environment-people interactions framework for analysing children's extra-curricular activities and active transport," Journal of Transport Geography, Elsevier, vol. 74(C), pages 341-358.
  12. Prateek Bansal & Vahid Keshavarzzadeh & Angelo Guevara & Shanjun Li & Ricardo A Daziano, 2022. "Designed quadrature to approximate integrals in maximum simulated likelihood estimation [Evaluating simulation-based approaches and multivariate quadrature on sparse grids in estimating multivariat," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 301-321.
  13. Batram, Manuel & Bauer, Dietmar, 2019. "On consistency of the MACML approach to discrete choice modelling," Journal of choice modelling, Elsevier, vol. 30(C), pages 1-16.
  14. Bhowmik, Tanmoy & Yasmin, Shamsunnahar & Eluru, Naveen, 2021. "A New Econometric Approach for Modeling Several Count Variables: A Case Study of Crash Frequency Analysis by Crash Type and Severity," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 172-203.
  15. Anna Gloria Billé & Samantha Leorato, 2017. "Quasi-ML estimation, Marginal Effects and Asymptotics for Spatial Autoregressive Nonlinear Models," BEMPS - Bozen Economics & Management Paper Series BEMPS44, Faculty of Economics and Management at the Free University of Bozen.
  16. Sikder, Sujan & Pinjari, Abdul Rawoof, 2013. "The benefits of allowing heteroscedastic stochastic distributions in multiple discrete-continuous choice models," Journal of choice modelling, Elsevier, vol. 9(C), pages 39-56.
  17. Carrión-Flores, Carmen E. & Flores-Lagunes, Alfonso & Guci, Ledia, 2018. "An estimator for discrete-choice models with spatial lag dependence using large samples, with an application to land-use conversions," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 77-93.
  18. Abay, Kibrom A. & Paleti, Rajesh & Bhat, Chandra R., 2013. "The joint analysis of injury severity of drivers in two-vehicle crashes accommodating seat belt use endogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 50(C), pages 74-89.
  19. Akshay Vij & Rico Krueger, 2018. "Random taste heterogeneity in discrete choice models: Flexible nonparametric finite mixture distributions," Papers 1802.02299, arXiv.org.
  20. 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.
  21. Khan, Mubassira & Machemehl, Randy, 2017. "Commercial vehicles time of day choice behavior in urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 68-83.
  22. Buddhavarapu, Prasad & Scott, James G. & Prozzi, Jorge A., 2016. "Modeling unobserved heterogeneity using finite mixture random parameters for spatially correlated discrete count data," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 492-510.
  23. González-Espejo, Felipe & Astroza, Sebastian & Hurtubia, Ricardo, 2022. "On the relation between school and residential location choice: Evidence of heterogeneous strategies from Santiago de Chile," Journal of Transport Geography, Elsevier, vol. 102(C).
  24. Paleti, Rajesh & Bhat, Chandra R., 2013. "The composite marginal likelihood (CML) estimation of panel ordered-response models," Journal of choice modelling, Elsevier, vol. 7(C), pages 24-43.
  25. Bhat, Chandra R. & Mondal, Aupal, 2022. "A New Flexible Generalized Heterogeneous Data Model (GHDM) with an Application to Examine the Effect of High Density Neighborhood Living on Bicycling Frequency," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 244-266.
  26. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Logit Mixture models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 185-198.
  27. Enam, Annesha & Konduri, Karthik C. & Pinjari, Abdul R. & Eluru, Naveen, 2018. "An integrated choice and latent variable model for multiple discrete continuous choice kernels: Application exploring the association between day level moods and discretionary activity engagement choi," Journal of choice modelling, Elsevier, vol. 26(C), pages 80-100.
  28. Allahviranloo, Mahdieh & Aissaoui, Leila, 2019. "A comparison of time-use behavior in metropolitan areas using pattern recognition techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 271-287.
  29. Watanabe, Hajime & Maruyama, Takuya, 2023. "A Bayesian instrumental variable model for multinomial choice with correlated alternatives," Journal of choice modelling, Elsevier, vol. 46(C).
  30. Mondal, Aupal & Bhat, Chandra R., 2022. "A spatial rank-ordered probit model with an application to travel mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 374-393.
  31. Bhat, Chandra R. & Astroza, Sebastian & Sidharthan, Raghuprasad & Alam, Mohammad Jobair Bin & Khushefati, Waleed H., 2014. "A joint count-continuous model of travel behavior with selection based on a multinomial probit residential density choice model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 31-51.
  32. Gopindra Sivakumar Nair & Sebastian Astroza & Chandra R. Bhat & Sara Khoeini & Ram M. Pendyala, 2018. "An application of a rank ordered probit modeling approach to understanding level of interest in autonomous vehicles," Transportation, Springer, vol. 45(6), pages 1623-1637, November.
  33. Adriano Alessandrini & Paolo Delle Site & Valerio Gatta & Edoardo Marcucci & Qing Zhang, 2015. "Stated Preference Logit Analysis Of Users’Attitudes Towards Conventional And Automated Buses," Working Papers 0215, CREI Università degli Studi Roma Tre, revised 2015.
  34. Bhat, Chandra R. & Pinjari, Abdul R. & Dubey, Subodh K. & Hamdi, Amin S., 2016. "On accommodating spatial interactions in a Generalized Heterogeneous Data Model (GHDM) of mixed types of dependent variables," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 240-263.
  35. Hamed Naseri & Edward Owen Douglas Waygood & Bobin Wang & Zachary Patterson, 2022. "Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters," IJERPH, MDPI, vol. 19(24), pages 1-19, December.
  36. Chandra R. Bhat & Subodh K. Dubey & Mohammad Jobair Bin Alam & Waleed H. Khushefati, 2015. "A New Spatial Multiple Discrete-Continuous Modeling Approach To Land Use Change Analysis," Journal of Regional Science, Wiley Blackwell, vol. 55(5), pages 801-841, November.
  37. Bhat, Chandra R., 2015. "A new generalized heterogeneous data model (GHDM) to jointly model mixed types of dependent variables," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 50-77.
  38. Chandra R. Bhat & Patrícia S. Lavieri, 2018. "A new mixed MNP model accommodating a variety of dependent non-normal coefficient distributions," Theory and Decision, Springer, vol. 84(2), pages 239-275, March.
  39. Bhat, Chandra R. & Astroza, Sebastian & Bhat, Aarti C. & Nagel, Kai, 2016. "Incorporating a multiple discrete-continuous outcome in the generalized heterogeneous data model: Application to residential self-selection effects analysis in an activity time-use behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 52-76.
  40. Xuemei Fu & Zhicai Juan, 2017. "Estimation of multinomial probit-kernel integrated choice and latent variable model: comparison on one sequential and two simultaneous approaches," Transportation, Springer, vol. 44(1), pages 91-116, January.
  41. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
  42. Dong, Chunjiao & Shao, Chunfu & Clarke, David B. & Nambisan, Shashi S., 2018. "An innovative approach for traffic crash estimation and prediction on accommodating unobserved heterogeneities," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 407-428.
  43. Lavieri, Patrícia S. & Bhat, Chandra R., 2019. "Modeling individuals’ willingness to share trips with strangers in an autonomous vehicle future," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 242-261.
  44. Dubey, Subodh & Cats, Oded & Hoogendoorn, Serge & Bansal, Prateek, 2022. "A multinomial probit model with Choquet integral and attribute cut-offs," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 140-163.
  45. Chandra R. Bhat & Rajesh Paleti & Palvinder Singh, 2014. "A Spatial Multivariate Count Model For Firm Location Decisions," Journal of Regional Science, Wiley Blackwell, vol. 54(3), pages 462-502, June.
  46. 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).
  47. Patil, Priyadarshan N. & Dubey, Subodh K. & Pinjari, Abdul R. & Cherchi, Elisabetta & Daziano, Ricardo & Bhat, Chandra R., 2017. "Simulation evaluation of emerging estimation techniques for multinomial probit models," Journal of choice modelling, Elsevier, vol. 23(C), pages 9-20.
  48. Xiong, Yingge & Mannering, Fred L., 2013. "The heterogeneous effects of guardian supervision on adolescent driver-injury severities: A finite-mixture random-parameters approach," Transportation Research Part B: Methodological, Elsevier, vol. 49(C), pages 39-54.
  49. Ipek Sener & Chandra Bhat, 2012. "Flexible spatial dependence structures for unordered multinomial choice models: formulation and application to teenagers’ activity participation," Transportation, Springer, vol. 39(3), pages 657-683, May.
  50. Brasington, David & Flores-Lagunes, Alfonso & Guci, Ledia, 2016. "A spatial model of school district open enrollment choice," Regional Science and Urban Economics, Elsevier, vol. 56(C), pages 1-18.
  51. Ricardo A. Daziano & Martin Achtnicht, 2014. "Forecasting Adoption of Ultra-Low-Emission Vehicles Using Bayes Estimates of a Multinomial Probit Model and the GHK Simulator," Transportation Science, INFORMS, vol. 48(4), pages 671-683, November.
  52. Cherchi, Elisabetta & Guevara, Cristian Angelo, 2012. "A Monte Carlo experiment to analyze the curse of dimensionality in estimating random coefficients models with a full variance–covariance matrix," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 321-332.
  53. Vinayak, Pragun & Dias, Felipe F. & Astroza, Sebastian & Bhat, Chandra R. & Pendyala, Ram M. & Garikapati, Venu M., 2018. "Accounting for multi-dimensional dependencies among decision-makers within a generalized model framework: An application to understanding shared mobility service usage levels," Transport Policy, Elsevier, vol. 72(C), pages 129-137.
  54. Lai, Xinjun & Lam, William H.K. & Su, Junbiao & Fu, Hui, 2019. "Modelling intra-household interactions in time-use and activity patterns of retired and dual-earner couples," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 172-194.
  55. Martinetti, Davide & Geniaux, Ghislain, 2017. "Approximate likelihood estimation of spatial probit models," Regional Science and Urban Economics, Elsevier, vol. 64(C), pages 30-45.
  56. Daziano, Ricardo A., 2015. "Inference on mode preferences, vehicle purchases, and the energy paradox using a Bayesian structural choice model," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 1-26.
  57. Sebastian Astroza & Venu M. Garikapati & Ram M. Pendyala & Chandra R. Bhat & Patricia L. Mokhtarian, 2019. "Representing heterogeneity in structural relationships among multiple choice variables using a latent segmentation approach," Transportation, Springer, vol. 46(5), pages 1755-1784, October.
  58. Bhat, Chandra R., 2018. "New matrix-based methods for the analytic evaluation of the multivariate cumulative normal distribution function," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 238-256.
  59. Bhat, Chandra R. & Dubey, Subodh K., 2014. "A new estimation approach to integrate latent psychological constructs in choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 68-85.
  60. Páez, Antonio & López, Fernando A. & Ruiz, Manuel & Morency, Catherine, 2013. "Development of an indicator to assess the spatial fit of discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 217-233.
  61. Weibo Li & Maria Kamargianni, 2020. "An Integrated Choice and Latent Variable Model to Explore the Influence of Attitudinal and Perceptual Factors on Shared Mobility Choices and Their Value of Time Estimation," Transportation Science, INFORMS, vol. 54(1), pages 62-83, January.
  62. Nobel, Anne & Lizin, Sebastien & Malina, Robert, 2023. "What drives the designation of protected areas? Accounting for spatial dependence using a composite marginal likelihood approach," Ecological Economics, Elsevier, vol. 205(C).
  63. Sarrias, Mauricio, 2021. "A two recursive equation model to correct for endogeneity in latent class binary probit models," Journal of choice modelling, Elsevier, vol. 40(C).
  64. Becker, Felix & Danaf, Mazen & Song, Xiang & Atasoy, Bilge & Ben-Akiva, Moshe, 2018. "Bayesian estimator for Logit Mixtures with inter- and intra-consumer heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 1-17.
  65. Chandra Bhat, 2015. "A new spatial (social) interaction discrete choice model accommodating for unobserved effects due to endogenous network formation," Transportation, Springer, vol. 42(5), pages 879-914, September.
  66. Bhat, Chandra R. & Dubey, Subodh K. & Nagel, Kai, 2015. "Introducing non-normality of latent psychological constructs in choice modeling with an application to bicyclist route choice," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 341-363.
  67. Nazneen Ferdous & Chandra Bhat, 2013. "A spatial panel ordered-response model with application to the analysis of urban land-use development intensity patterns," Journal of Geographical Systems, Springer, vol. 15(1), pages 1-29, January.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.