IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v39y2024i6d10.1007_s00180-023-01408-7.html
   My bibliography  Save this article

A general stream sampling design

Author

Listed:
  • Bardia Panahbehagh

    (Kharazmi University
    University of Neuchâtel)

  • Raphaël Jauslin

    (Kharazmi University)

  • Yves Tillé

    (University of Neuchâtel)

Abstract

With the emergence of the big data era, the need for sampling methods that select samples based on the order of the observed units is felt more than ever. In order to meet this necessity, a new sequential unequal probability sampling method is proposed. The decision to select or not each unit is made based on the order in which the units appear. A variant of this method allows a selection of a sample from a stream. This method consists in using sliding windows which are a kind of strata of controllable size. This method also allows the sample to be spread in a controlled manner throughout the population. A special case of the method with windows of size one leads to deciding on each sampling unit immediately after observing it. The implementation of size one windows is simple and will be presented here based on an algorithm with a single condition. Also, by selecting the windows of size two, we will have one of the optimal stream sampling methods, which results in a well-spread stream sample with positive second-order inclusion probabilities.

Suggested Citation

  • Bardia Panahbehagh & Raphaël Jauslin & Yves Tillé, 2024. "A general stream sampling design," Computational Statistics, Springer, vol. 39(6), pages 2899-2924, September.
    • Handle: RePEc:spr:compst:v:39:y:2024:i:6:d:10.1007_s00180-023-01408-7
    DOI: 10.1007/s00180-023-01408-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00180-023-01408-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00180-023-01408-7?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. A. B. Sunter, 1977. "List Sequential Sampling with Equal or Unequal Probabilities Without Replacement," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 26(3), pages 261-268, November.
    2. Raphaël Jauslin & Yves Tillé, 2020. "Spatial Spread Sampling Using Weakly Associated Vectors," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(3), pages 431-451, September.
    3. Raphaël Jauslin & Bardia Panahbehagh & Yves Tillé, 2022. "Sequential spatially balanced sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 33(8), December.
    4. Anton Grafström & Niklas L. P. Lundström & Lina Schelin, 2012. "Spatially Balanced Sampling through the Pivotal Method," Biometrics, The International Biometric Society, vol. 68(2), pages 514-520, June.
    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. Raphaël Jauslin & Bardia Panahbehagh & Yves Tillé, 2022. "Sequential spatially balanced sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 33(8), December.
    2. G. Alleva & G. Arbia & P. D. Falorsi & V. Nardelli & A. Zuliani, 2023. "Optimal two-stage spatial sampling design for estimating critical parameters of SARS-CoV-2 epidemic: Efficiency versus feasibility," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 983-999, September.
    3. Sara Franceschi & Rosa Maria Di Biase & Agnese Marcelli & Lorenzo Fattorini, 2022. "Some Empirical Results on Nearest-Neighbour Pseudo-populations for Resampling from Spatial Populations," Stats, MDPI, vol. 5(2), pages 1-16, April.
    4. Yves Tillé, 2022. "Some Solutions Inspired by Survey Sampling Theory to Build Effective Clinical Trials," International Statistical Review, International Statistical Institute, vol. 90(3), pages 481-498, December.
    5. Wilmer Prentius, 2024. "Locally correlated Poisson sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 35(2), March.
    6. Tomasz Bąk, 2021. "Spatial sampling methods modified by model use," Statistics in Transition New Series, Polish Statistical Association, vol. 22(2), pages 143-154, June.
    7. Lorenzo Fattorini & Timothy G. Gregoire & Sara Trentini, 2018. "The Use of Calibration Weighting for Variance Estimation Under Systematic Sampling: Applications to Forest Cover Assessment," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(3), pages 358-373, September.
    8. Pommerening, Arne & Szmyt, Janusz & Zhang, Gongqiao, 2020. "A new nearest-neighbour index for monitoring spatial size diversity: The hyperbolic tangent index," Ecological Modelling, Elsevier, vol. 435(C).
    9. Maxime Dumont & Guilhem Brunel & Paul Tresson & Jérôme Nespoulous & Hassan Boukcim & Marc Ducousso & Stéphane Boivin & Olivier Taugourdeau & Bruno Tisseyre, 2024. "Operational sampling designs for poorly accessible areas based on a multi-objective optimization method," Post-Print hal-04566087, HAL.
    10. Huan Xie & Fang Wang & Yali Gong & Xiaohua Tong & Yanmin Jin & Ang Zhao & Chao Wei & Xinyi Zhang & Shicheng Liao, 2022. "Spatially Balanced Sampling for Validation of GlobeLand30 Using Landscape Pattern-Based Inclusion Probability," Sustainability, MDPI, vol. 14(5), pages 1-19, February.
    11. Linda Altieri & Daniela Cocchi, 2021. "Spatial Sampling for Non‐compact Patterns," International Statistical Review, International Statistical Institute, vol. 89(3), pages 532-549, December.
    12. Robertson, Blair & Price, Chris, 2024. "One point per cluster spatially balanced sampling," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
    13. B. L. Robertson & O. Ozturk & O. Kravchuk & J. A. Brown, 2022. "Spatially Balanced Sampling with Local Ranking," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(4), pages 622-639, December.
    14. Jacopo Paglia & Jo Eidsvik & Juha Karvanen, 2022. "Efficient spatial designs using Hausdorff distances and Bayesian optimization," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1060-1084, September.
    15. Schelin, Lina & Sjöstedt-de Luna, Sara, 2014. "Spatial prediction in the presence of left-censoring," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 125-141.
    16. Robertson, B.L. & McDonald, T. & Price, C.J. & Brown, J.A., 2017. "A modification of balanced acceptance sampling," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 107-112.
    17. Xin Zhao & Anton Grafström, 2024. "Estimation of change with partially overlapping and spatially balanced samples," Environmetrics, John Wiley & Sons, Ltd., vol. 35(1), February.
    18. Guillaume Chauvet & Ronan Le Gleut, 2021. "Inference under pivotal sampling: Properties, variance estimation, and application to tesselation for spatial sampling," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 108-131, March.
    19. Cindy L. Yu & Jie Li & Michael G. Karl & Todd J. Krueger, 2020. "Obtaining a Balanced Area Sample for the Bureau of Land Management Rangeland Survey," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(2), pages 250-275, June.
    20. R. Benedetti & F. Piersimoni & P. Postiglione, 2017. "Alternative and complementary approaches to spatially balanced samples," METRON, Springer;Sapienza Università di Roma, vol. 75(3), pages 249-264, December.

    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:spr:compst:v:39:y:2024:i:6:d:10.1007_s00180-023-01408-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.