IDEAS home Printed from https://ideas.repec.org/r/eee/econom/v124y2005i2p311-334.html
   My bibliography  Save this item

A Bayesian analysis of the multinomial probit model using marginal data augmentation

Citations

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


Cited by:

  1. Sylvia Kaufmann, 2014. "K-state switching models with time-varying transition distributions – Does credit growth signal stronger effects of variables on inflation?," Working Papers 14.04, Swiss National Bank, Study Center Gerzensee.
  2. Gómez Ramos, Almudena & Bardají Azcaráte, Isabel & Atance Muñiz, Ignacio, 2006. "The role of geographical labelling in inserting extensive cattle systems into beef marketing channels. Evidence from three Spanish case studies," Cahiers d'Economie et de Sociologie Rurales (CESR), Institut National de la Recherche Agronomique (INRA), vol. 78.
  3. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Fast variational Bayes methods for multinomial probit models," Papers 2202.12495, arXiv.org, revised Oct 2022.
  4. Robert Zeithammer & Peter Lenk, 2006. "Bayesian estimation of multivariate-normal models when dimensions are absent," Quantitative Marketing and Economics (QME), Springer, vol. 4(3), pages 241-265, September.
  5. Sumeetpal S. Singh & Nicolas Chopin & Nick Whiteley, 2010. "Bayesian Learning of Noisy Markov Decision Processes," Working Papers 2010-36, Center for Research in Economics and Statistics.
  6. Michelle Sovinsky & Liana Jacobi & Alessandra Allocca & Tao Sun, 2024. "More than Joints: Multi-Substance Use, Choice Limitations, and Policy Implications," CRC TR 224 Discussion Paper Series crctr224_2024_501, University of Bonn and University of Mannheim, Germany.
  7. Jianmei ZHAO, 2014. "Rural income diversification patterns and their determinants in China," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 60(5), pages 219-231.
  8. Pan, Yan & Jing, Yunteng & Wu, Tonghai & Kong, Xiangxing, 2022. "Knowledge-based data augmentation of small samples for oil condition prediction," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
  9. Berrett, Candace & Calder, Catherine A., 2012. "Data augmentation strategies for the Bayesian spatial probit regression model," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 478-490.
  10. Christopher Steven Marcum, 2011. "Age Differences in Daily Social Activities," Working Papers WR-904, RAND Corporation.
  11. Duncan Fong & Sunghoon Kim & Zhe Chen & Wayne DeSarbo, 2016. "A Bayesian Multinomial Probit MODEL FOR THE ANALYSIS OF PANEL CHOICE DATA," Psychometrika, Springer;The Psychometric Society, vol. 81(1), pages 161-183, March.
  12. Almudena Gómez Ramos & Isabel Bardají Azcaráte & Ignacio Atance Muñiz, 2006. "The role of geographical labelling in inserting extensive cattle systems into beef marketing channels. Evidence from three Spanish case studies," Cahiers d'Economie et Sociologie Rurales, INRA Department of Economics, vol. 78, pages 81-105.
  13. Chiew, Esther & Daziano, Ricardo A., 2016. "A Bayes multinomial probit model for random consumer-surplus maximization," Journal of choice modelling, Elsevier, vol. 21(C), pages 56-59.
  14. Burda, Martin & Harding, Matthew & Hausman, Jerry, 2008. "A Bayesian mixed logit-probit model for multinomial choice," Journal of Econometrics, Elsevier, vol. 147(2), pages 232-246, December.
  15. Veyssiere, Luc Pierre, 2009. "A three essays dissertation on agricultural and environmental microeconomics," ISU General Staff Papers 200901010800001958, Iowa State University, Department of Economics.
  16. Måns Magnusson & Leif Jonsson & Mattias Villani, 2020. "DOLDA: a regularized supervised topic model for high-dimensional multi-class regression," Computational Statistics, Springer, vol. 35(1), pages 175-201, March.
  17. Michael O'Kelly & John Doyle & Philip J. Boland, 2010. "How many ways can you look at a proportion?: cross‐community vote transfers in Northern Ireland after the Belfast Agreement," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 215-235, January.
  18. Bon Sang Koo, 2023. "When legislators responded to news media surveys: unstable responses, missing not at random responses, and self-censorship," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1821-1843, April.
  19. Park, Sang Soo & Lee, Chung-Ki, 2011. "베이지안 추정법을 이용한 주택선택의 다항프로빗 모형 분석 [Analysis of housing choice using multinomial probit model – Bayesian estimation]," MPRA Paper 37150, University Library of Munich, Germany.
  20. Raja Chakir & Olivier Parent, 2009. "Determinants of land use changes: A spatial multinomial probit approach," Papers in Regional Science, Wiley Blackwell, vol. 88(2), pages 327-344, June.
  21. Michelle Sovinsky & Liana Jacobi & Alessandra Allocca & Tao Sun, 2023. "More than Joints: Multi-Substance Use, Choice Limitations, and Policy Implications," Rationality and Competition Discussion Paper Series 487, CRC TRR 190 Rationality and Competition.
  22. Harald Hruschka, 2007. "Using a heterogeneous multinomial probit model with a neural net extension to model brand choice," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(2), pages 113-127.
  23. Kim, Changjoo & Parent, Olivier, 2016. "Modeling individual travel behaviors based on intra-household interactions," Regional Science and Urban Economics, Elsevier, vol. 57(C), pages 1-11.
  24. Caffo, Brian & An, Ming-Wen & Rohde, Charles, 2007. "Flexible random intercept models for binary outcomes using mixtures of normals," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5220-5235, July.
  25. Conti, Gabriella & Frühwirth-Schnatter, Sylvia & Heckman, James J. & Piatek, Rémi, 2014. "Bayesian exploratory factor analysis," Journal of Econometrics, Elsevier, vol. 183(1), pages 31-57.
  26. Zhang, Xiao & Boscardin, W. John & Belin, Thomas R., 2008. "Bayesian analysis of multivariate nominal measures using multivariate multinomial probit models," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3697-3708, March.
  27. Almudena Gómez Ramos & Isabel Bardají Azcaráte & Ignacio Atance Muñiz, 2006. "The role of geographical labelling in inserting extensive cattle systems into beef marketing channels. Evidence from three Spanish case studies," Post-Print hal-01201119, HAL.
  28. Ruben Loaiza-Maya & Didier Nibbering, 2020. "Scalable Bayesian Estimation in the Multinomial Probit Model," Monash Econometrics and Business Statistics Working Papers 25/20, Monash University, Department of Econometrics and Business Statistics.
  29. Annamaria Lusardi & Pierre-Carl Michaud & Olivia S. Mitchell, 2011. "Optimal Financial Literacy and Saving for Retirement," Working Papers 905, RAND Corporation.
  30. Morrison, Mark & Bergland, Olvar, 2006. "Prospects for the use of choice modelling for benefit transfer," Ecological Economics, Elsevier, vol. 60(2), pages 420-428, December.
  31. Rico Krueger & Michel Bierlaire & Thomas Gasos & Prateek Bansal, 2020. "Robust discrete choice models with t-distributed kernel errors," Papers 2009.06383, arXiv.org, revised Dec 2022.
  32. Didier Nibbering, 2019. "A High-dimensional Multinomial Choice Model," Monash Econometrics and Business Statistics Working Papers 19/19, Monash University, Department of Econometrics and Business Statistics.
  33. Wang, Xiaokun (Cara) & Kockelman, Kara M. & Lemp, Jason D., 2012. "The dynamic spatial multinomial probit model: analysis of land use change using parcel-level data," Journal of Transport Geography, Elsevier, vol. 24(C), pages 77-88.
  34. Johannes Reichl & Sylvia Frühwirth-Schnatter, 2012. "A censored random coefficients model for the detection of zero willingness to pay," Quantitative Marketing and Economics (QME), Springer, vol. 10(2), pages 259-281, June.
  35. Keith Burghardt & Emanuel F Alsina & Michelle Girvan & William Rand & Kristina Lerman, 2017. "The myopia of crowds: Cognitive load and collective evaluation of answers on Stack Exchange," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-19, March.
  36. Ricardo A. Daziano & Luis Miranda-Moreno & Shahram Heydari, 2013. "Computational Bayesian Statistics in Transportation Modeling: From Road Safety Analysis to Discrete Choice," Transport Reviews, Taylor & Francis Journals, vol. 33(5), pages 570-592, September.
  37. Zachary K. Collier & Walter L. Leite & Allison Karpyn, 2021. "Neural Networks to Estimate Generalized Propensity Scores for Continuous Treatment Doses," Evaluation Review, , vol. 45(1-2), pages 3-33, February.
  38. Christopher Marcum, 2011. "Age Differences in Daily Social Activities," Working Papers 904, RAND Corporation.
  39. Schliep, Erin M. & Hoeting, Jennifer A., 2015. "Data augmentation and parameter expansion for independent or spatially correlated ordinal data," Computational Statistics & Data Analysis, Elsevier, vol. 90(C), pages 1-14.
  40. Xin-Yuan Song & Zhao-Hua Lu & Jing-Heng Cai & Edward Ip, 2013. "A Bayesian Modeling Approach for Generalized Semiparametric Structural Equation Models," Psychometrika, Springer;The Psychometric Society, vol. 78(4), pages 624-647, October.
  41. Veettil, Prakashan Chellattan & Speelman, Stijn & Frija, Aymen & Buysse, Jeroen & van Huylenbroeck, Guido, 2011. "Complementarity between water pricing, water rights and local water governance: A Bayesian analysis of choice behaviour of farmers in the Krishna river basin, India," Ecological Economics, Elsevier, vol. 70(10), pages 1756-1766, August.
  42. 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.
  43. Phillip Li, 2018. "Efficient MCMC estimation of inflated beta regression models," Computational Statistics, Springer, vol. 33(1), pages 127-158, March.
  44. Zhehan Jiang & Jonathan Templin, 2019. "Gibbs Samplers for Logistic Item Response Models via the Pólya–Gamma Distribution: A Computationally Efficient Data-Augmentation Strategy," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 358-374, June.
  45. Speelman, Stijn & Veettil, Prakashan Chellatan, 2012. "Comparing the scope for irrigation water rights reforms in India and South Africa," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126731, International Association of Agricultural Economists.
  46. Lamoureux, Christopher G. & Nejadmalayeri, Ali, 2015. "Costs of capital and public issuance choice," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 27-45.
  47. Chu, Amanda M.Y. & Omori, Yasuhiro & So, Hing-yu & So, Mike K.P., 2023. "A Multivariate Randomized Response Model for Sensitive Binary Data," Econometrics and Statistics, Elsevier, vol. 27(C), pages 16-35.
  48. Fabio Blasutto & Egor Kozlov, 2020. "(Changing) Marriage and Cohabitation Patterns in the US: do Divorce Laws Matter?," 2020 Papers pbl245, Job Market Papers.
  49. Moffa, Giusi & Kuipers, Jack, 2014. "Sequential Monte Carlo EM for multivariate probit models," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 252-272.
  50. 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.
  51. Dogan, Osman & Taspinar, Suleyman, 2016. "Bayesian Inference in Spatial Sample Selection Models," MPRA Paper 82829, University Library of Munich, Germany.
  52. Ben D'Exelle & Els Lecoutere & Bjorn Van Campenhout, 2010. "Social status and bargaining when resources are scarce: Evidence from a field lab experiment," Working Paper series, University of East Anglia, Centre for Behavioural and Experimental Social Science (CBESS) 10-09, School of Economics, University of East Anglia, Norwich, UK..
  53. Malefaki, Sonia & Iliopoulos, George, 2007. "Simulating from a multinomial distribution with large number of categories," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5471-5476, August.
  54. Terrence D. Jorgensen & Aditi M. Bhangale & Yves Rosseel, 2024. "Two-Stage Limited-Information Estimation for Structural Equation Models of Round-Robin Variables," Stats, MDPI, vol. 7(1), pages 1-34, February.
  55. Piatek, Rémi & Gensowski, Miriam, 2017. "A Multinomial Probit Model with Latent Factors: Identification and Interpretation without a Measurement System," IZA Discussion Papers 11042, Institute of Labor Economics (IZA).
  56. Jeong, Seonghyun & Park, Minjae & Park, Taeyoung, 2017. "Analysis of binary longitudinal data with time-varying effects," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 145-153.
  57. 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.
  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. Uddin, Md Nazir & Gaskins, Jeremy T., 2023. "Shared Bayesian variable shrinkage in multinomial logistic regression," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
  60. repec:bfi:wpaper:2014-014 is not listed on IDEAS
  61. Ding, Peng, 2014. "Bayesian robust inference of sample selection using selection-t models," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 451-464.
  62. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
  63. Hahn, Eugene D., 2006. "Link function selection in stochastic multicriteria decision making models," European Journal of Operational Research, Elsevier, vol. 172(1), pages 86-100, July.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.