Skip to main content

A Test for Truncation Invariant Dependence

  • Conference paper
  • First Online:
Soft Methods for Data Science (SMPS 2016)

Abstract

A test is proposed to check whether a random sample comes from a truncation invariant copula C, that is, if C is the copula of a pair (UV) of random variables uniformly distributed on [0, 1], then C is also the copula of the conditional distribution function of \((U,V\mid U\le \alpha )\) for every \(\alpha \in (0,1]\). The asymptotic normality of the test statistics is shown. Moreover, a procedure is described to simplify the approximation of the asymptotic variance of the test. Its performance is investigated in a simulation study.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Berghaus B, Bücher A (2014) Nonparametric tests for tail monotonicity. J Econom 180(2):117–126

    Article  MathSciNet  MATH  Google Scholar 

  2. Bücher A, Dette H, Volgushev S (2011) New estimators of the Pickands dependence function and a test for extreme-value dependence. Ann Stat 39(4):1963–2006

    Article  MathSciNet  MATH  Google Scholar 

  3. Bücher A, Dette H, Volgushev S (2012) A test for Archimedeanity in bivariate copula models. J Multivar Anal 110:121–132

    Article  MathSciNet  MATH  Google Scholar 

  4. Di Lascio FML, Durante F, Jaworski P (2016) Truncation invariant copulas and a testing procedure. J Stat Comput Simul 86(12):2362–2378. doi:10.1080/00949655.2015.1110820

  5. Durante F, Jaworski P (2012) Invariant dependence structure under univariate truncation. Statistics 46(2):263–277

    Article  MathSciNet  MATH  Google Scholar 

  6. Durante F, Jaworski P, Mesiar R (2011) Invariant dependence structures and Archimedean copulas. Stat Probab Lett 81(12):1995–2003

    Article  MathSciNet  MATH  Google Scholar 

  7. Fermanian JD (2013) An overview of the goodness-of-fit test problem for copulas. In: Jaworski P, Durante F, Härdle W (eds) Copulae in mathematical and quantitative finance. Lecture notes in statistics. Springer, Berlin, Heidelberg, pp 61–89

    Google Scholar 

  8. Genest C, Rémillard B, Beaudoin D (2009) Goodness-of-fit tests for copulas: a review and a power study. Insur Math Econ 44(2):199–213

    Article  MathSciNet  MATH  Google Scholar 

  9. Genest C, Kojadinovic I, Nešlehová J, Yan J (2011) A goodness-of-fit test for bivariate extreme-value copulas. Bernoulli 17(1):253–275

    Article  MathSciNet  MATH  Google Scholar 

  10. Ghoudi K, Rémillard B (2004) Empirical processes based on pseudo-observations. II. The multivariate case. In: Horváth L, Szyszkowicz B (eds) Asymptotic methods in stochastics, vol 44. Fields Institute Communications, American Mathematical Society, Providence, RI, pp 381–406. Proceedings of the international conference (ICAMS’02) held at Carleton University, Ottawa, ON, 23–25 May 2002

    Google Scholar 

  11. Gijbels I, Sznajder D (2013) Testing tail monotonicity by constrained copula estimation. Insur Math Econ 52(2):338–351

    Article  MathSciNet  MATH  Google Scholar 

  12. Gijbels I, Omelka M, Sznajder D (2010) Positive quadrant dependence tests for copulas. Can J Stat 38(4):555–581

    Article  MathSciNet  MATH  Google Scholar 

  13. Jaworski P (2010) Testing archimedeanity. In: Borgelt C, González-Rogríguez G, Trutschnig W, Lubiano M, Gil M, Grzegorzewski P, Hryniewicz O (eds) Combining soft computing and statistical methods in data analysis. Advances in intelligent and soft computing, vol 77. Springer, Berlin, pp 353–360

    Google Scholar 

  14. Jaworski P (2013) Invariant dependence structure under univariate truncation: the high-dimensional case. Statistics 47(5):1064–1074

    Article  MathSciNet  MATH  Google Scholar 

  15. Jaworski P (2013) The limiting properties of copulas under univariate conditioning. In: Jaworski P, Durante F, Härdle WK (eds) Copulae in mathematical and quantitative finance. Lecture notes in statistics. Springer, Berlin, Heidelberg, pp 129–163

    Google Scholar 

  16. Kojadinovic I, Segers J, Yan J (2011) Large-sample tests of extreme-value dependence for multivariate copulas. Can J Stat 39(4):703–720

    Article  MathSciNet  MATH  Google Scholar 

  17. van der Vaart AW, Wellner JA (1996) Weak convergence and empirical processes. Springer series in statistics. Springer, New York

    Google Scholar 

Download references

Acknowledgments

We would like to thank Bruno Rémillard for many useful comments about the asymptotic behavior of our test procedure. The authors have been supported by Free University of Bozen-Bolzano, Italy, via the projects COCCO and MODEX. The third author acknowledges the support from National Science Centre, Poland, under project 2015/17/B/HS4/00911.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Piotr Jaworski .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing Switzerland

About this paper

Cite this paper

Di Lascio, F.M.L., Durante, F., Jaworski, P. (2017). A Test for Truncation Invariant Dependence. In: Ferraro, M., et al. Soft Methods for Data Science. SMPS 2016. Advances in Intelligent Systems and Computing, vol 456. Springer, Cham. https://doi.org/10.1007/978-3-319-42972-4_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-42972-4_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42971-7

  • Online ISBN: 978-3-319-42972-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics