IDEAS home Printed from https://ideas.repec.org/p/tiu/tiutis/0bb67ddc-0dd1-4c13-9916-5a83a9ead2f4.html
   My bibliography  Save this paper

The Shorth Plot

Author

Listed:
  • Einmahl, J.H.J.

    (Tilburg University, School of Economics and Management)

  • Gantner, M.

    (Tilburg University, School of Economics and Management)

  • Sawitzki, G.

Abstract

No abstract is available for this item.

Suggested Citation

  • Einmahl, J.H.J. & Gantner, M. & Sawitzki, G., 2010. "The Shorth Plot," Other publications TiSEM 0bb67ddc-0dd1-4c13-9916-5, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:0bb67ddc-0dd1-4c13-9916-5a83a9ead2f4
    as

    Download full text from publisher

    File URL: https://pure.uvt.nl/ws/portalfiles/portal/1088778/jcgs.shorth-plot.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Einmahl, J. H.J. & Mason, D.M., 1992. "Generalized quantile processes," Other publications TiSEM b2a76bac-045d-457f-869f-d, Tilburg University, School of Economics and Management.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. John H. J. Einmahl & Laurens Haan & Chen Zhou, 2016. "Statistics of heteroscedastic extremes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 31-51, January.
    2. Einmahl, John & Segers, Johan, 2020. "Empirical Tail Copulas for Functional Data," Other publications TiSEM edc722e6-cc70-4221-87a2-8, Tilburg University, School of Economics and Management.
    3. Aigner, Maximilian & Chavez-Demoulin, Valérie & Guillou, Armelle, 2022. "Measuring and comparing risks of different types," Insurance: Mathematics and Economics, Elsevier, vol. 102(C), pages 1-21.

    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. Barme-Delcroix, Marie-Francoise & Gather, Ursula, 2007. "Limit laws for multidimensional extremes," Statistics & Probability Letters, Elsevier, vol. 77(18), pages 1750-1755, December.
    2. Croux, Christophe & Haesbroeck, Gentiane, 1997. "An easy way to increase the finite-sample efficiency of the resampled minimum volume ellipsoid estimator," Computational Statistics & Data Analysis, Elsevier, vol. 25(2), pages 125-141, July.
    3. Alexander Zaigraev & Magdalena Alama-Bućko, 2018. "Optimal choice of order statistics under confidence region estimation in case of large samples," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(3), pages 283-305, April.
    4. Nadja Klein & Thomas Kneib, 2020. "Directional bivariate quantiles: a robust approach based on the cumulative distribution function," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(2), pages 225-260, June.
    5. Alexander Zaigraev & Magdalena Alama-Bućko, 2013. "On optimal choice of order statistics in large samples for the construction of confidence regions for the location and scale," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(4), pages 577-593, May.
    6. Ryan Janicki & Tucker S. McElroy, 2016. "Hermite expansion and estimation of monotonic transformations of Gaussian data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(1), pages 207-234, March.
    7. Beirlant, J. & Buitendag, S. & del Barrio, E. & Hallin, M. & Kamper, F., 2020. "Center-outward quantiles and the measurement of multivariate risk," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 79-100.
    8. Wang, Jin & Serfling, Robert, 2006. "Influence functions for a general class of depth-based generalized quantile functions," Journal of Multivariate Analysis, Elsevier, vol. 97(4), pages 810-826, April.
    9. Justel, Ana & Peña, Daniel & Zamar, Rubén, 1997. "A multivariate Kolmogorov-Smirnov test of goodness of fit," Statistics & Probability Letters, Elsevier, vol. 35(3), pages 251-259, October.
    10. Baíllo, Amparo, 2003. "Total error in a plug-in estimator of level sets," DES - Working Papers. Statistics and Econometrics. WS ws032806, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Polonik, Wolfgang & Yao, Qiwei, 2002. "Set-Indexed Conditional Empirical and Quantile Processes Based on Dependent Data," Journal of Multivariate Analysis, Elsevier, vol. 80(2), pages 234-255, February.
    12. Baíllo, Amparo, 2003. "Total error in a plug-in estimator of level sets," Statistics & Probability Letters, Elsevier, vol. 65(4), pages 411-417, December.
    13. Polonik, Wolfgang, 1997. "Minimum volume sets and generalized quantile processes," Stochastic Processes and their Applications, Elsevier, vol. 69(1), pages 1-24, July.
    14. Serfling, Robert, 2002. "Generalized Quantile Processes Based on Multivariate Depth Functions, with Applications in Nonparametric Multivariate Analysis," Journal of Multivariate Analysis, Elsevier, vol. 83(1), pages 232-247, October.
    15. Wang, Jin, 2019. "Asymptotics of generalized depth-based spread processes and applications," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 363-380.
    16. Mulubrhan G. Haile & Lingling Zhang & David J. Olive, 2024. "Predicting Random Walks and a Data-Splitting Prediction Region," Stats, MDPI, vol. 7(1), pages 1-11, January.
    17. Vladimir I. Koltchinskii, 1998. "Differentiability of Inverse Operators and Limit Theorems for Inverse Functions," Journal of Theoretical Probability, Springer, vol. 11(3), pages 645-699, July.
    18. J. Beirlant & A. Berlinet & G. Biau, 2008. "Higher order estimation at Lebesgue points," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(3), pages 651-677, September.
    19. Beirlant, J. & Mason, D. M. & Vynckier, C., 1999. "Goodness-of-fit analysis for multivariate normality based on generalized quantiles," Computational Statistics & Data Analysis, Elsevier, vol. 30(2), pages 119-142, April.
    20. Di Bucchianico, A. & Einmahl, J.H.J. & Mushkudiani, N.A., 2001. "Smallest nonparametric tolerance regions," Other publications TiSEM 436f9be2-d0ad-49af-b6df-9, Tilburg University, School of Economics and Management.

    More about this item

    Statistics

    Access and download statistics

    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:tiu:tiutis:0bb67ddc-0dd1-4c13-9916-5a83a9ead2f4. 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: Richard Broekman (email available below). General contact details of provider: https://www.tilburguniversity.edu/about/schools/economics-and-management/ .

    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.