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Estimation of Copula Models With Discrete Margins via Bayesian Data Augmentation

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Cited by:

  1. Azam, Kazim & Pitt, Michael, 2014. "Bayesian Inference for a Semi-Parametric Copula-based Markov Chain," Economic Research Papers 270232, University of Warwick - Department of Economics.
  2. Li, Feng & Kang, Yanfei, 2018. "Improving forecasting performance using covariate-dependent copula models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 456-476.
  3. Pravin Trivedi & David Zimmer, 2017. "A Note on Identification of Bivariate Copulas for Discrete Count Data," Econometrics, MDPI, vol. 5(1), pages 1-11, February.
  4. Marta Nai Ruscone & Daniel Fernández, 2021. "Dynamics of HDI Index: Temporal Dependence Based on D-vine Copulas Model for Three-Way Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 158(2), pages 563-593, December.
  5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  6. Juan Wu & Xue Wang & Stephen G. Walker, 2014. "Bayesian Nonparametric Inference for a Multivariate Copula Function," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 747-763, September.
  7. Kazim Azam & Andre Lucas, 2015. "Mixed Density based Copula Likelihood," Tinbergen Institute Discussion Papers 15-003/IV/DSF084, Tinbergen Institute.
  8. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
  9. Azam, Kazim & Pitt, Michael, 2014. "Bayesian Inference for a Semi-Parametric Copula-based Markov Chain," The Warwick Economics Research Paper Series (TWERPS) 1051, University of Warwick, Department of Economics.
  10. Stöber, Jakob & Hong, Hyokyoung Grace & Czado, Claudia & Ghosh, Pulak, 2015. "Comorbidity of chronic diseases in the elderly: Patterns identified by a copula design for mixed responses," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 28-39.
  11. Huihui Lin & N. Rao Chaganty, 2021. "Multivariate distributions of correlated binary variables generated by pair-copulas," Journal of Statistical Distributions and Applications, Springer, vol. 8(1), pages 1-14, December.
  12. Jeffrey Racine, 2015. "Mixed data kernel copulas," Empirical Economics, Springer, vol. 48(1), pages 37-59, February.
  13. Elizabeth D. Schifano & Himchan Jeong & Ved Deshpande & Dipak K. Dey, 2021. "Fully and empirical Bayes approaches to estimating copula-based models for bivariate mixed outcomes using Hamiltonian Monte Carlo," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 133-152, March.
  14. Calabrese, Raffaella & Degl’Innocenti, Marta & Osmetti, Silvia Angela, 2017. "The effectiveness of TARP-CPP on the US banking industry: A new copula-based approach," European Journal of Operational Research, Elsevier, vol. 256(3), pages 1029-1037.
  15. Ruben Loaiza-Maya & Michael Stanley Smith, 2017. "Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series," Papers 1712.09150, arXiv.org, revised Jul 2018.
  16. Marchese, Scott & Diao, Guoqing, 2017. "Density ratio model for multivariate outcomes," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 249-261.
  17. Zilko, Aurelius A. & Kurowicka, Dorota, 2016. "Copula in a multivariate mixed discrete–continuous model," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 28-55.
  18. Michael Stanley Smith, 2021. "Implicit Copulas: An Overview," Papers 2109.04718, arXiv.org.
  19. Salaheddine El Adlouni, 2018. "Quantile regression C-vine copula model for spatial extremes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(1), pages 299-317, October.
  20. Xiaotian Zheng & Athanasios Kottas & Bruno Sansó, 2023. "Bayesian geostatistical modeling for discrete‐valued processes," Environmetrics, John Wiley & Sons, Ltd., vol. 34(7), November.
  21. F. Louzada & P. H. Ferreira, 2016. "Modified inference function for margins for the bivariate clayton copula-based SUN Tobit Model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(16), pages 2956-2976, December.
  22. Sun, Can & Bie, Zhaohong & Xie, Min & Jiang, Jiangfeng, 2016. "Fuzzy copula model for wind speed correlation and its application in wind curtailment evaluation," Renewable Energy, Elsevier, vol. 93(C), pages 68-76.
  23. L. L. Henn, 2022. "Limitations and performance of three approaches to Bayesian inference for Gaussian copula regression models of discrete data," Computational Statistics, Springer, vol. 37(2), pages 909-946, April.
  24. Smith, Michael Stanley, 2023. "Implicit Copulas: An Overview," Econometrics and Statistics, Elsevier, vol. 28(C), pages 81-104.
  25. Rebecca Graziani & Sergio Venturini, 2020. "A Bayesian approach to discrete multiple outcome network meta-analysis," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-17, April.
  26. Zichen Ma & Shannon W. Davis & Yen‐Yi Ho, 2023. "Flexible copula model for integrating correlated multi‐omics data from single‐cell experiments," Biometrics, The International Biometric Society, vol. 79(2), pages 1559-1572, June.
  27. Juliana Schulz & Christian Genest & Mhamed Mesfioui, 2021. "A multivariate Poisson model based on comonotonic shocks," International Statistical Review, International Statistical Institute, vol. 89(2), pages 323-348, August.
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