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Multipurpose Estimation from Unbalanced Samples

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  • P. Bardsley
  • R. L. Chambers

Abstract

The problem of estimation in multipurpose sample surveys is treated from the prediction theory viewpoint. In particular the interaction of sample imbalance and collinearity among the survey predictor variables is explored and a ridge type estimation technique is developed which optimises the tradeoff between bias and variance for this situation. An application to a survey carried out by the Bureau of Agricultural Economics is given.

Suggested Citation

  • P. Bardsley & R. L. Chambers, 1984. "Multipurpose Estimation from Unbalanced Samples," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 33(3), pages 290-299, November.
    • Handle: RePEc:bla:jorssc:v:33:y:1984:i:3:p:290-299
    DOI: 10.2307/2347706
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    Cited by:

    1. Alessio Guandalini & Claudio Ceccarelli, 2022. "Impact measurement and dimension reduction of auxiliary variables in calibration estimator using the Shapley decomposition," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 759-784, October.
    2. Miller, Elton N. & Andrews, Gregory, 1993. "Factors influencing landholders' investments in soil conservation activities," 1993 Conference (37th), February 9-11, 1993, Sydney, Australia 147759, Australian Agricultural and Resource Economics Society.
    3. Park, Mingue & Cho, HyungJun, 2008. "Minimum MSE regression estimator with estimated population quantities of auxiliary variables," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 394-404, December.
    4. Jean-Francois Beaumont & Cynthia Bocci, 2008. "Another look at ridge calibration," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 5-20.

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