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Copula in a multivariate mixed discrete–continuous model

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  • Zilko, Aurelius A.
  • Kurowicka, Dorota

Abstract

The use of different copula-based models to represent the joint distribution of an eight-dimensional mixed discrete and continuous problem consisting of five discrete and three continuous variables is investigated. The discussion starts with the theoretical properties of the copula-based models. Four different models are constructed for the data collected for the purpose of predicting the length of disruption caused by problems with the train detection system in the Dutch railway network and their performance is tested. The more complex models turn out to represent the data better. Nevertheless, it is shown that the simpler eight dimensional Normal copula still constitutes a statistically sound model for the data.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:csdana:v:103:y:2016:i:c:p:28-55
    DOI: 10.1016/j.csda.2016.02.017
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    References listed on IDEAS

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    5. Michael S. Smith & Mohamad A. Khaled, 2012. "Estimation of Copula Models With Discrete Margins via Bayesian Data Augmentation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 290-303, March.
    6. Peter X.-K. Song & Mingyao Li & Ying Yuan, 2009. "Joint Regression Analysis of Correlated Data Using Gaussian Copulas," Biometrics, The International Biometric Society, vol. 65(1), pages 60-68, March.
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    8. 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.
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    Cited by:

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    4. Woraphon Yamaka & Paravee Maneejuk & Rungrapee Phadkantha & Wiranya Puntoon & Payap Tarkhamtham & Tatcha Sudtasan, 2023. "Survival and Duration Analysis of MSMEs in Chiang Mai, Thailand: Evidence from the Post-COVID-19 Recovery," Mathematics, MDPI, vol. 11(4), pages 1-21, February.
    5. Weiping Zhang & MengMeng Zhang & Yu Chen, 2020. "A Copula-Based GLMM Model for Multivariate Longitudinal Data with Mixed-Types of Responses," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(2), pages 353-379, November.
    6. Geenens Gery, 2020. "Copula modeling for discrete random vectors," Dependence Modeling, De Gruyter, vol. 8(1), pages 417-440, January.

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    Keywords

    Copula; Vine; Mixed models;
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