IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v62y2000i1p89-94.html
   My bibliography  Save this article

The exact bootstrap mean and variance of an L‐estimator

Author

Listed:
  • A. D. Hutson
  • M. D. Ernst

Abstract

Exact analytic expressions for the bootstrap mean and variance of any L‐estimator are obtained, thus eliminating the error due to bootstrap resampling. The expressions follow from the direct calculation of the bootstrap mean vector and covariance matrix of the whole set of order statistics. By using these expressions, recommendations can be made about the appropriateness of bootstrap estimation under given conditions.

Suggested Citation

  • A. D. Hutson & M. D. Ernst, 2000. "The exact bootstrap mean and variance of an L‐estimator," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(1), pages 89-94.
    • Handle: RePEc:bla:jorssb:v:62:y:2000:i:1:p:89-94
    DOI: 10.1111/1467-9868.00221
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1467-9868.00221
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1467-9868.00221?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
    ---><---

    Citations

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


    Cited by:

    1. Lauer, Alexandra & Zähle, Henryk, 2017. "Bootstrap consistency and bias correction in the nonparametric estimation of risk measures of collective risks," Insurance: Mathematics and Economics, Elsevier, vol. 74(C), pages 99-108.
    2. Kim, Joseph H.T., 2010. "Bias correction for estimated distortion risk measure using the bootstrap," Insurance: Mathematics and Economics, Elsevier, vol. 47(2), pages 198-205, October.
    3. Hutson, Alan D., 2000. "Estimating the covariance of bivariate order statistics with applications," Statistics & Probability Letters, Elsevier, vol. 48(2), pages 195-203, June.
    4. Diane L. Evans & Lawrence M. Leemis & John H. Drew, 2006. "The Distribution of Order Statistics for Discrete Random Variables with Applications to Bootstrapping," INFORMS Journal on Computing, INFORMS, vol. 18(1), pages 19-30, February.
    5. Dimitris Bertsimas & Bradley Sturt, 2020. "Computation of Exact Bootstrap Confidence Intervals: Complexity and Deterministic Algorithms," Operations Research, INFORMS, vol. 68(3), pages 949-964, May.
    6. Gámiz, Maria Luz & Nozal-Cañadas, Rafael & Raya-Miranda, Rocío, 2020. "TTT-SiZer: A graphic tool for aging trends recognition," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    7. Brodin, Erik, 2006. "On quantile estimation by bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 50(6), pages 1398-1406, March.
    8. Michael R. Dugas & Francisco J. Samaniego, 2007. "On optimal system designs in reliability‐economics frameworks," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(5), pages 568-582, August.
    9. Alan Hutson, 2000. "A composite quantile function estimator with applications in bootstrapping," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(5), pages 567-577.
    10. Alan Hutson, 2009. "A distribution function estimator for the difference of order statistics from two independent samples," Statistical Papers, Springer, vol. 50(1), pages 203-208, January.
    11. Elamir, Elsayed A. H. & Seheult, Allan H., 2003. "Trimmed L-moments," Computational Statistics & Data Analysis, Elsevier, vol. 43(3), pages 299-314, July.
    12. Cseres-Gergely, Zsombor & Kvedaras, Virmantas, 2019. "Change and convergence of income distributions in the European Union during 2007-2014," JRC Working Papers in Economics and Finance 2019-13, Joint Research Centre, European Commission.
    13. Gabriel Montes Rojas & Andrés Sebastián Mena, 2020. "Density estimation using bootstrap quantile variance and quantile-mean covariance," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2020-50, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    14. Álvarez, Adolfo, 2009. "Recombining dependent data: an Order Statistics," DES - Working Papers. Statistics and Econometrics. WS ws098526, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Modarres, Reza & Hui, Terrence P. & Zheng, Gang, 2006. "Resampling methods for ranked set samples," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1039-1050, November.
    16. Kvedaras, Virmantas & Cseres-Gergely, Zsombor, 2020. "Convergence of income distributions: Total and inequality-affecting changes in the EU," Economics Letters, Elsevier, vol. 188(C).

    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:bla:jorssb:v:62:y:2000:i:1:p:89-94. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.