IDEAS home Printed from https://ideas.repec.org/a/bla/istatr/v80y2012i1p127-148.html
   My bibliography  Save this article

On the Generalized Bootstrap for Sample Surveys with Special Attention to Poisson Sampling

Author

Listed:
  • Jean‐François Beaumont
  • Zdenek Patak

Abstract

No abstract is available for this item.

Suggested Citation

  • Jean‐François Beaumont & Zdenek Patak, 2012. "On the Generalized Bootstrap for Sample Surveys with Special Attention to Poisson Sampling," International Statistical Review, International Statistical Institute, vol. 80(1), pages 127-148, April.
    • Handle: RePEc:bla:istatr:v:80:y:2012:i:1:p:127-148
    DOI: j.1751-5823.2011.00166.x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1751-5823.2011.00166.x
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/j.1751-5823.2011.00166.x?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.

    Citations

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


    Cited by:

    1. Xu Mengxuan & Landsman Victoria & Graubard Barry I., 2021. "Estimation of Domain Means from Business Surveys in the Presence of Stratum Jumpers and Nonresponse," Journal of Official Statistics, Sciendo, vol. 37(4), pages 1059-1078, December.
    2. Beaumont, Jean-François & Charest, Anne-Sophie, 2012. "Bootstrap variance estimation with survey data when estimating model parameters," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4450-4461.
    3. Daniela Marella & Paola Vicard, 2022. "Bayesian network structural learning from complex survey data: a resampling based approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 981-1013, October.
    4. Żądło Tomasz, 2021. "On the generalisation of Quatember’s bootstrap," Statistics in Transition New Series, Polish Statistical Association, vol. 22(1), pages 163-178, March.
    5. Heng Chen & Rallye Shen, 2017. "The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Calibration for Single-Location Retailers," Technical Reports 109, Bank of Canada.
    6. Marie-Hélène Felt & David Laferrière, 2020. "Sample Calibration of the Online CFM Survey," Technical Reports 118, Bank of Canada.
    7. Jean-Francois Beaumont & J. N. K. Rao, 2019. "Comments on: Deville and Särndal’s calibration: revisiting a 25 years old successful optimization problem," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(4), pages 1071-1076, December.
    8. Pier Luigi Conti & Fulvia Mecatti, 2022. "Resampling under Complex Sampling Designs: Roots, Development and the Way Forward," Stats, MDPI, vol. 5(1), pages 1-12, March.
    9. Jean-François Beaumont & Nelson Émond, 2022. "A Bootstrap Variance Estimation Method for Multistage Sampling and Two-Phase Sampling When Poisson Sampling Is Used at the Second Phase," Stats, MDPI, vol. 5(2), pages 1-19, March.
    10. Zhonglei Wang & Liuhua Peng & Jae Kwang Kim, 2022. "Bootstrap inference for the finite population mean under complex sampling designs," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1150-1174, September.
    11. Erika Antal & Yves Tillé, 2014. "A new resampling method for sampling designs without replacement: the doubled half bootstrap," Computational Statistics, Springer, vol. 29(5), pages 1345-1363, October.
    12. Wayne A. Fuller & Jason C. Legg & Yang Li, 2017. "Bootstrap Variance Estimation for Rejective Sampling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1562-1570, October.
    13. Sixia Chen & David Haziza & Zeinab Mashreghi, 2022. "A Comparison of Existing Bootstrap Algorithms for Multi-Stage Sampling Designs," Stats, MDPI, vol. 5(2), pages 1-17, June.
    14. Tomasz Żądło, 2021. "On the generalisation of Quatember's bootstrap," Statistics in Transition New Series, Polish Statistical Association, vol. 22(1), pages 163-178, March.
    15. Marius Stefan & Michael A. Hidiroglou, 2023. "A Bootstrap Variance Procedure for the Generalised Regression Estimator," International Statistical Review, International Statistical Institute, vol. 91(2), pages 294-317, August.

    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:istatr:v:80:y:2012:i:1:p:127-148. 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/isiiinl.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.