IDEAS home Printed from https://ideas.repec.org/a/spr/jagbes/v23y2018i3d10.1007_s13253-018-0325-x.html
   My bibliography  Save this article

The Use of Calibration Weighting for Variance Estimation Under Systematic Sampling: Applications to Forest Cover Assessment

Author

Listed:
  • Lorenzo Fattorini

    (University of Siena)

  • Timothy G. Gregoire

    (Yale University)

  • Sara Trentini

    (University of Siena)

Abstract

The purpose of this note is to propose a variance estimator under non-measurable designs that exploits the existence of an auxiliary variable well correlated with the survey variable of interest. Under non-measurable designs, the Sen–Yates–Grundy variance estimator generates a downward bias that can be reduced using a calibration weighting based on the auxiliary variable. Conditions of approximate unbiasedness for the resulting calibration estimator are given. The application to systematic sampling is considered. The proposal proves to be effective for estimating the variance of the forest cover estimator in remote sensing-based surveys, owing to the strong correlation between the reference data, available from a systematic sample, and the satellite map data, available for the whole population and hence exploited as an auxiliary variable. Supplementary materials accompanying this paper appear online.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:jagbes:v:23:y:2018:i:3:d:10.1007_s13253-018-0325-x
    DOI: 10.1007/s13253-018-0325-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13253-018-0325-x
    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/s13253-018-0325-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.

    References listed on IDEAS

    as
    1. 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.
    2. Stevens, Don L. & Olsen, Anthony R., 2004. "Spatially Balanced Sampling of Natural Resources," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 262-278, January.
    3. Lorenzo Fattorini, 2006. "Applying the Horvitz-Thompson criterion in complex designs: A computer-intensive perspective for estimating inclusion probabilities," Biometrika, Biometrika Trust, vol. 93(2), pages 269-278, June.
    4. Jean D. Opsomer & Mario Francisco-Fernández & Xiaoxi Li, 2012. "Model-Based Non-parametric Variance Estimation for Systematic Sampling," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 39(3), pages 528-542, September.
    5. Giorgio Montanari & Francesco Bartolucci, 1998. "On estimating the variance of the systematic sample mean," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 7(2), pages 185-196, August.
    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. 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.
    2. Maria Michela Dickson & Giuseppe Espa & Lorenzo Fattorini & Flavio Santi, 2022. "Double-calibration estimators accounting for under-coverage and nonresponse in socio-economic surveys," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1273-1288, December.

    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. ak Tomasz B, 2021. "Spatial sampling methods modified by model use," Statistics in Transition New Series, Polish Statistical Association, vol. 22(2), pages 143-154, June.
    2. 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.
    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. Linda Altieri & Daniela Cocchi, 2021. "Spatial Sampling for Non‐compact Patterns," International Statistical Review, International Statistical Institute, vol. 89(3), pages 532-549, December.
    5. Robertson, Blair & Price, Chris, 2024. "One point per cluster spatially balanced sampling," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
    6. 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.
    7. 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.
    8. Giuseppe Espa & Diego Giuliani & Flavio Santi & Emanuele Taufer, 2017. "Model-based variance estimation in two-dimensional systematic sampling," METRON, Springer;Sapienza Università di Roma, vol. 75(3), pages 265-275, December.
    9. 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.
    10. Lorenzo Fattorini & Alberto Meriggi & Enrico Merli & Paolo Varuzza, 2020. "Sampling Strategies to Estimate Deer Density by Drive Counts," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(2), pages 168-185, June.
    11. Wilmer Prentius, 2024. "Locally correlated Poisson sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 35(2), March.
    12. 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).
    13. Raphaël Jauslin & Bardia Panahbehagh & Yves Tillé, 2022. "Sequential spatially balanced sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 33(8), December.
    14. 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.
    15. 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.
    16. 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.
    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. 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.
    19. 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.
    20. Roberto Benedetti & Federica Piersimoni & Paolo Postiglione, 2017. "Spatially Balanced Sampling: A Review and A Reappraisal," International Statistical Review, International Statistical Institute, vol. 85(3), pages 439-454, 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:jagbes:v:23:y:2018:i:3:d:10.1007_s13253-018-0325-x. 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.