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Bayesian Non- and Semi-parametric Methods and Applications

Citations

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Cited by:

  1. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2023. "Forecasting with a panel Tobit model," Quantitative Economics, Econometric Society, vol. 14(1), pages 117-159, January.
  2. Gordon Anderson, Alessio Farcomeni, Maria Grazia Pittau and Roberto Zelli, 2019. "Multidimensional Nation Wellbeing, More Equal yet More Polarized: An Analysis of the Progress of Human Development Since 1990," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 44(1), pages 1-22, March.
  3. Laura Liu, 2018. "Density Forecasts in Panel Data Models : A Semiparametric Bayesian Perspective," Finance and Economics Discussion Series 2018-036, Board of Governors of the Federal Reserve System (U.S.).
  4. Burghardt, Elliot & Sewell, Daniel & Cavanaugh, Joseph, 2022. "Agglomerative and divisive hierarchical Bayesian clustering," Computational Statistics & Data Analysis, Elsevier, vol. 176(C).
  5. Max J. Pachali & Peter Kurz & Thomas Otter, 0. "How to generalize from a hierarchical model?," Quantitative Marketing and Economics (QME), Springer, vol. 0, pages 1-38.
  6. Ana Cristina Pereira Das Neves, 2018. "The Mass Media Transmission Of Central Bank Communication Under Uncertainty," Anais do XLIV Encontro Nacional de Economia [Proceedings of the 44th Brazilian Economics Meeting] 54, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
  7. Matthew Dimick & Daniel Stegmueller, 2015. "The Political Economy of Risk and Ideology," SOEPpapers on Multidisciplinary Panel Data Research 809, DIW Berlin, The German Socio-Economic Panel (SOEP).
  8. Sparnaaij, Martijn & Yuan, Yufei & Daamen, Winnie & Duives, Dorine C., 2024. "Using pedestrian modelling to inform virus transmission mitigation policies: A novel activity scheduling model to enable virus transmission risk assessment in a restaurant environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
  9. Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Incorporating Search and Sales Information in Demand Estimation," Cowles Foundation Discussion Papers 2313, Cowles Foundation for Research in Economics, Yale University.
  10. Hyowon Kim & Greg M. Allenby, 2022. "Integrating Textual Information into Models of Choice and Scaled Response Data," Marketing Science, INFORMS, vol. 41(4), pages 815-830, July.
  11. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
  12. Laura Liu, 2017. "Density Forecasts in Panel Models: A semiparametric Bayesian Perspective," PIER Working Paper Archive 17-006, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 28 Apr 2017.
  13. Simonov, Andrey & Rao, Justin, 2017. "Demand for (Un)Biased News: The Role of Government Control in Online News Markets," Working Papers 261, The University of Chicago Booth School of Business, George J. Stigler Center for the Study of the Economy and the State.
  14. Wayne Taylor & Anand Bodapati, 2024. "The Effect of Gambling Outcomes on Casino Return Times with Scalable DDC," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 11(1), pages 1-28, December.
  15. Max J. Pachali & Peter Kurz & Thomas Otter, 2020. "How to generalize from a hierarchical model?," Quantitative Marketing and Economics (QME), Springer, vol. 18(4), pages 343-380, December.
  16. Jean-Marie Dufour & Richard Luger, 2017. "Identification-robust moment-based tests for Markov switching in autoregressive models," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 713-727, October.
  17. Philipp Aschersleben & Winfried J. Steiner, 2022. "A semiparametric approach to estimating reference price effects in sales response models," Journal of Business Economics, Springer, vol. 92(4), pages 591-643, May.
  18. Weber, Anett & Steiner, Winfried J., 2021. "Modeling price response from retail sales: An empirical comparison of models with different representations of heterogeneity," European Journal of Operational Research, Elsevier, vol. 294(3), pages 843-859.
  19. Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Incorporating Search and Sales Information in Demand Estimation," Cowles Foundation Discussion Papers 2313R1, Cowles Foundation for Research in Economics, Yale University, revised Mar 2023.
  20. Ozonder, Gozde & Miller, Eric J., 2021. "Longitudinal investigation of skeletal activity episode timing decisions – A copula approach," Journal of choice modelling, Elsevier, vol. 40(C).
  21. Gordon Anderson & Thomas Fruehauf & Maria Grazia Pittau & Roberto Zelli, 2015. "Evaluating Progress Toward an Equal Opportunity Goal: Assessing the German Educational Reforms of the First Decade of the 21st Century," Working Papers tecipa-552, University of Toronto, Department of Economics.
  22. Gordon Anderson & Maria Grazia Pittau & Roberto Zelli, 2020. "Measuring the progress of equality of educational opportunity in absence of cardinal comparability," METRON, Springer;Sapienza Università di Roma, vol. 78(2), pages 155-174, August.
  23. Caio Waisman, 2024. "Bayesian estimation of finite mixtures of Tobit models," Papers 2411.09771, arXiv.org.
  24. Rilling, Benedikt & Kurz, Peter & Herbes, Carsten, 2024. "Renewable gases in the heating market: Identifying consumer preferences through a Discrete Choice Experiment," Energy Policy, Elsevier, vol. 184(C).
  25. Anoek Castelein & Dennis Fok & Richard Paap, 2020. "Heterogeneous variable selection in nonlinear panel data models: A semiparametric Bayesian approach," Tinbergen Institute Discussion Papers 20-061/III, Tinbergen Institute.
  26. Namin, Aidin & Dehdashti, Yashar, 2019. "A “hidden†side of consumer grocery shopping choice," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 16-27.
  27. Ryan Dew & Asim Ansari, 2018. "Bayesian Nonparametric Customer Base Analysis with Model-Based Visualizations," Marketing Science, INFORMS, vol. 37(2), pages 216-235, March.
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