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Locally correlated Poisson sampling

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  • Wilmer Prentius

Abstract

Designs that produces spatially balanced, or well‐spread, samples are desirable as they increase the probability of obtaining a sample highly representative of the population. Spatially correlated Poisson sampling (SCPS) is a method for selecting well‐spread samples. In the SCPS method, the sampling outcomes (inclusion or exclusion of units) are decided sequentially. After each decision, the inclusion probabilities of surrounding units are updated. A specific order for deciding the sampling outcomes is not enforced for SCPS, that is, the order can be chosen randomly or be fixed. A new modified method called locally correlated Poisson sampling (LCPS) is suggested. In this new method, the order of the decisions makes sure the inclusion probabilities are updated (more) locally. As a result, a stronger negative correlation between inclusion indicators of nearby units is achieved. Simulations on various data sets show that the resulting samples from LCPS, in general, are more spatially balanced and produce lower variance than samples from SCPS and the local pivotal method.

Suggested Citation

  • Wilmer Prentius, 2024. "Locally correlated Poisson sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 35(2), March.
    • Handle: RePEc:wly:envmet:v:35:y:2024:i:2:n:e2832
    DOI: 10.1002/env.2832
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    References listed on IDEAS

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    1. Lennart Bondesson & Daniel Thorburn, 2008. "A List Sequential Sampling Method Suitable for Real‐Time Sampling," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(3), pages 466-483, September.
    2. B. L. Robertson & J. A. Brown & T. McDonald & P. Jaksons, 2013. "BAS: Balanced Acceptance Sampling of Natural Resources," Biometrics, The International Biometric Society, vol. 69(3), pages 776-784, September.
    3. 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.
    4. Anton Grafström & Yves Tillé, 2013. "Doubly balanced spatial sampling with spreading and restitution of auxiliary totals," Environmetrics, John Wiley & Sons, Ltd., vol. 24(2), pages 120-131, March.
    5. 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.
    6. Roberto Benedetti & Federica Piersimoni & Paolo Postiglione, 2015. "Sampling Spatial Units for Agricultural Surveys," Advances in Spatial Science, Springer, edition 127, number 978-3-662-46008-5.
    7. Anton Grafström & Lina Schelin, 2014. "How to Select Representative Samples," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 277-290, June.
    8. Raphaël Jauslin & Bardia Panahbehagh & Yves Tillé, 2022. "Sequential spatially balanced sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 33(8), December.
    9. Xin Zhao & Anton Grafström, 2020. "A sample coordination method to monitor totals of environmental variables," Environmetrics, John Wiley & Sons, Ltd., vol. 31(6), September.
    10. Jean-Claude Deville & Yves Tille, 2004. "Efficient balanced sampling: The cube method," Biometrika, Biometrika Trust, vol. 91(4), pages 893-912, December.
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