IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v211y2024ics0167715224001135.html
   My bibliography  Save this article

Strong uniform laws of large numbers for bootstrap means and other randomly weighted sums

Author

Listed:
  • Spencer, Neil A.
  • Miller, Jeffrey W.

Abstract

This article establishes novel strong uniform laws of large numbers for randomly weighted sums such as bootstrap means. By leveraging recent advances, these results extend previous work in their general applicability to a wide range of weighting procedures and in their flexibility with respect to the effective bootstrap sample size. In addition to the standard multinomial bootstrap and the m-out-of-n bootstrap, our results apply to a large class of randomly weighted sums involving negatively orthant dependent (NOD) weights, including the Bayesian bootstrap, jackknife, resampling without replacement, simple random sampling with over-replacement, independent weights, and multivariate Gaussian weighting schemes. Weights are permitted to be non-identically distributed and possibly even negative. Our proof technique is based on extending a proof of the i.i.d. strong uniform law of large numbers to employ strong laws for randomly weighted sums; in particular, we exploit a recent Marcinkiewicz–Zygmund strong law for NOD weighted sums.

Suggested Citation

  • Spencer, Neil A. & Miller, Jeffrey W., 2024. "Strong uniform laws of large numbers for bootstrap means and other randomly weighted sums," Statistics & Probability Letters, Elsevier, vol. 211(C).
    • Handle: RePEc:eee:stapro:v:211:y:2024:i:c:s0167715224001135
    DOI: 10.1016/j.spl.2024.110144
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715224001135
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2024.110144?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. Antal, Erika & Tillé, Yves, 2011. "A Direct Bootstrap Method for Complex Sampling Designs From a Finite Population," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 534-543.
    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. Luca Sartore & Kelly Toppin & Linda Young & Clifford Spiegelman, 2019. "Developing Integer Calibration Weights for Census of Agriculture," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(1), pages 26-48, March.
    2. Enrico Fabrizi & Caterina Giusti & Nicola Salvati & Nikos Tzavidis, 2014. "Mapping average equivalized income using robust small area methods," Papers in Regional Science, Wiley Blackwell, vol. 93(3), pages 685-701, August.
    3. 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.
    4. Sayed A. Mostafa & Ibrahim A. Ahmad, 2021. "Kernel Density Estimation Based on the Distinct Units in Sampling with Replacement," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 507-547, November.
    5. Zhao, Puying & Haziza, David & Wu, Changbao, 2020. "Survey weighted estimating equation inference with nuisance functionals," Journal of Econometrics, Elsevier, vol. 216(2), pages 516-536.
    6. Pier Luigi Conti & Alberto Iorio & Alessio Guandalini & Daniela Marella & Paola Vicard & Vincenzina Vitale, 2020. "On the estimation of the Lorenz curve under complex sampling designs," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 1-24, March.
    7. 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.
    8. 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.
    9. Michal Brzezinski, 2014. "Statistical inference for richness measures," Applied Economics, Taylor & Francis Journals, vol. 46(14), pages 1599-1608, May.
    10. Alessio Guandalini, 2022. "Things you should know about the Gini index," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 76(4), pages 4-12, October-D.
    11. J. A. Mayor-Gallego & J. L. Moreno-Rebollo & M. D. Jiménez-Gamero, 2019. "Estimation of the finite population distribution function using a global penalized calibration method," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(1), pages 1-35, March.
    12. 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.
    13. María del Mar Rueda & Beatriz Cobo & Antonio Arcos, 2021. "Regression Models in Complex Survey Sampling for Sensitive Quantitative Variables," Mathematics, MDPI, vol. 9(6), pages 1-13, March.
    14. Żądło Tomasz, 2021. "On the generalisation of Quatember’s bootstrap," Statistics in Transition New Series, Statistics Poland, 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.
    16. Michal Brzezinski, 2011. "Variance Estimation for Richness Measures," LWS Working papers 11, LIS Cross-National Data Center in Luxembourg.
    17. Conti, Pier Luigi & Mecatti, Fulvia & Nicolussi, Federica, 2022. "Efficient unequal probability resampling from finite populations," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
    18. Pier Luigi Conti & Daniela Marella, 2015. "Inference for Quantiles of a Finite Population: Asymptotic versus Resampling Results," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 545-561, June.
    19. 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.
    20. 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.

    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:eee:stapro:v:211:y:2024:i:c:s0167715224001135. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.