IDEAS home Printed from https://ideas.repec.org/a/spr/stmapp/v31y2022i5d10.1007_s10260-022-00628-3.html
   My bibliography  Save this article

Selection of mixed copula for association modeling with tied observations

Author

Listed:
  • Yang Li

    (Renmin University of China
    Renmin University of China
    Renmin University of China)

  • Fan Wang

    (Renmin University of China
    Renmin University of China)

  • Ye Shen

    (University of Georgia)

  • Yichen Qin

    (University of Cincinnati)

  • Jiesheng Si

    (Hangzhou Dianzi University)

Abstract

The link between Obesity and Hypertension is among the most popular topics which have been explored in medical research in recent decades. However, it is challenging to establish the relationship comprehensively and accurately because the distribution of BMI and blood pressure is usually fat tailed and severely tied. In this paper, we propose a data-driven copulas selection approach via penalized likelihood which can deal with tied data by interval censoring estimation. Minimax Concave Penalty is involved to perform the unbiased selection of mixed copula model for its convergence property to get un-penalized solution. Interval censoring and maximizing pseudo-likelihood, inspired from survival analysis, is introduced by considering ranks as intervals with upper and lower limits. This paper describes the model and corresponding iterative algorithm. Simulations to compare the proposed approach versus existing methods in different scenarios are presented. Additionally, the proposed method is also applied to the association modeling on the China Health and Nutrition Survey (CHNS) data. Both numerical studies and real data analysis reveal good performance of the proposed method.

Suggested Citation

  • Yang Li & Fan Wang & Ye Shen & Yichen Qin & Jiesheng Si, 2022. "Selection of mixed copula for association modeling with tied observations," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1127-1180, December.
    • Handle: RePEc:spr:stmapp:v:31:y:2022:i:5:d:10.1007_s10260-022-00628-3
    DOI: 10.1007/s10260-022-00628-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10260-022-00628-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10260-022-00628-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    2. Pudney, Stephen & Hernandez-Alava, Monica, 2016. "Copula-based modelling of self-reported health states: an application to the use of EQ-5D-3L and EQ-5D-5L in evaluating drug therapies for rheumatic disease," ISER Working Paper Series 2016-04, Institute for Social and Economic Research.
    3. Zongwu Cai & Xian Wang, 2014. "Selection of Mixed Copula Model via Penalized Likelihood," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 788-801, June.
    4. Ribeiro, Andreia F.S. & Russo, Ana & Gouveia, Célia M. & Páscoa, Patrícia, 2019. "Copula-based agricultural drought risk of rainfed cropping systems," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    5. Ling Hu, 2006. "Dependence patterns across financial markets: a mixed copula approach," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 717-729.
    6. Medovikov, Ivan, 2016. "When does the stock market listen to economic news? New evidence from copulas and news wires," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 27-40.
    7. Kojadinovic, Ivan & Yan, Jun, 2010. "Modeling Multivariate Distributions with Continuous Margins Using the copula R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i09).
    8. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2011. "International diversification: A copula approach," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 403-417, February.
    9. Shegorika Rajwani & Dilip Kumar, 2019. "Measuring Dependence Between the USA and the Asian Economies: A Time-varying Copula Approach," Global Business Review, International Management Institute, vol. 20(4), pages 962-980, August.
    10. Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
    11. Yang Li & Rong Li & Yichen Qin & Mengyun Wu & Shuangge Ma, 2019. "Integrative interaction analysis using threshold gradient directed regularization," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(2), pages 354-375, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zongwu Cai & Xian Wang, 2014. "Selection of Mixed Copula Model via Penalized Likelihood," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 788-801, June.
    2. Zongwu Cai & Guannan Liu & Wei Long & Xuelong Luo, 2024. "Semiparametric Conditional Mixture Copula Models with Copula Selection," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202401, University of Kansas, Department of Economics, revised Jan 2024.
    3. repec:kan:wpaper:202105 is not listed on IDEAS
    4. Mokni, Khaled & Mansouri, Faysal, 2017. "Conditional dependence between international stock markets: A long memory GARCH-copula model approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 116-131.
    5. Boubaker, Heni & Sghaier, Nadia, 2013. "Portfolio optimization in the presence of dependent financial returns with long memory: A copula based approach," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 361-377.
    6. Bingduo Yang & Zongwu Cai & Christian M. Hafner & Guannan Liu, 2018. "Trending Mixture Copula Models with Copula Selection," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201809, University of Kansas, Department of Economics, revised Sep 2018.
    7. Chiu-Lan Chang & Paul L. Hsueh, 2013. "An Investigation of the Flight-to-Quality Effect: Evidence from Asia-Pacific Countries," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S4), pages 53-69, September.
    8. Okhrin, Ostap & Ristig, Alexander & Sheen, Jeffrey R. & Trück, Stefan, 2015. "Conditional systemic risk with penalized copula," SFB 649 Discussion Papers 2015-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2013. "Estimating non-linear serial and cross-interdependence between financial assets," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 837-846.
    10. Okhrin, Ostap & Ristig, Alexander, 2014. "Hierarchical Archimedean Copulae: The HAC Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i04).
    11. Guannan Liu & Wei Long & Bingduo Yang & Zongwu Cai, 2022. "Semiparametric estimation and model selection for conditional mixture copula models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 287-330, March.
    12. Hofert, Marius & Mächler, Martin & McNeil, Alexander J., 2012. "Likelihood inference for Archimedean copulas in high dimensions under known margins," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 133-150.
    13. Grundke, Peter & Polle, Simone, 2012. "Crisis and risk dependencies," European Journal of Operational Research, Elsevier, vol. 223(2), pages 518-528.
    14. Delatte, Anne-Laure & Lopez, Claude, 2013. "Commodity and equity markets: Some stylized facts from a copula approach," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5346-5356.
    15. repec:hum:wpaper:sfb649dp2012-036 is not listed on IDEAS
    16. Mensah, Jones Odei & Premaratne, Gamini, 2014. "Dependence patterns among Banking Sectors in Asia: A Copula Approach," MPRA Paper 60119, University Library of Munich, Germany.
    17. Heni Boubaker & Nadia Sghaier, 2015. "On the Dynamic Dependence between US and other Developed Stock Markets: An Extreme-value Time-varying Copula Approach," Bankers, Markets & Investors, ESKA Publishing, issue 136-137, pages 80-93, May-June.
    18. Barry K. Goodwin & Matthew T. Holt & Gülcan Önel & Jeffrey P. Prestemon, 2018. "Copula-based nonlinear modeling of the law of one price for lumber products," Empirical Economics, Springer, vol. 54(3), pages 1237-1265, May.
    19. Federico Pasquale Cortese, 2019. "Tail Dependence in Financial Markets: A Dynamic Copula Approach," Risks, MDPI, vol. 7(4), pages 1-14, November.
    20. Marcelo Brutti Righi & Paulo Sergio Ceretta, 2012. "Predicting the risk of global portfolios considering the non-linear dependence structures," Economics Bulletin, AccessEcon, vol. 32(1), pages 282-294.
    21. Marcelo Brutti Righi & Paulo Sergio Ceretta, 2011. "Extreme values dependence of risk in Latin American markets," Economics Bulletin, AccessEcon, vol. 31(4), pages 2903-2914.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stmapp:v:31:y:2022:i:5:d:10.1007_s10260-022-00628-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.