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A fast algorithm for balanced sampling

Author

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  • Guillaume Chauvet
  • Yves Tillé

Abstract

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Suggested Citation

  • Guillaume Chauvet & Yves Tillé, 2006. "A fast algorithm for balanced sampling," Computational Statistics, Springer, vol. 21(1), pages 53-62, March.
    • Handle: RePEc:spr:compst:v:21:y:2006:i:1:p:53-62
    DOI: 10.1007/s00180-006-0250-2
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    Citations

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    Cited by:

    1. Hervé Cardot & Camelia Goga & Pauline Lardin, 2014. "Variance Estimation and Asymptotic Confidence Bands for the Mean Estimator of Sampled Functional Data with High Entropy Unequal Probability Sampling Designs," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 516-534, June.
    2. 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.
    3. Maria Michela Dickson & Yves Tillé, 2016. "Ordered spatial sampling by means of the traveling salesman problem," Computational Statistics, Springer, vol. 31(4), pages 1359-1372, December.
    4. R. Benedetti & M. S. Andreano & F. Piersimoni, 2019. "Sample selection when a multivariate set of size measures is available," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(1), pages 1-25, March.
    5. Leuenberger, Michael & Eustache, Esther & Jauslin, Raphaël & Tillé, Yves, 2022. "Balancing a sample almost perfectly," Statistics & Probability Letters, Elsevier, vol. 180(C).
    6. Aubry, Philippe & Francesiaz, Charlotte & Guillemain, Matthieu, 2024. "On the impact of preferential sampling on ecological status and trend assessment," Ecological Modelling, Elsevier, vol. 492(C).
    7. Berger, Yves G. & Patilea, Valentin, 2022. "A semi-parametric empirical likelihood approach for conditional estimating equations under endogenous selection," Econometrics and Statistics, Elsevier, vol. 24(C), pages 151-163.
    8. Hasler, Caren & Tillé, Yves, 2014. "Fast balanced sampling for highly stratified population," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 81-94.
    9. Chauvet, Guillaume & Do Paco, Wilfried, 2018. "Exact balanced random imputation for sample survey data," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 1-16.
    10. Raphaël Jauslin & Bardia Panahbehagh & Yves Tillé, 2022. "Sequential spatially balanced sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 33(8), December.
    11. Roberto Benedetti & Maria Michela Dickson & Giuseppe Espa & Francesco Pantalone & Federica Piersimoni, 2022. "A simulated annealing-based algorithm for selecting balanced samples," Computational Statistics, Springer, vol. 37(1), pages 491-505, March.
    12. Kaeding, Matthias, 2016. "Fast, approximate MCMC for Bayesian analysis of large data sets: A design based approach," Ruhr Economic Papers 660, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    13. 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.

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