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An Estimation of Sensitive Attribute Applying Geometric Distribution under Probability Proportional to Size Sampling

Author

Listed:
  • Gi-Sung Lee

    (Department of Children Welfare, Woosuk University, Wanju Jeonbuk 55338, Korea)

  • Ki-Hak Hong

    (Department of Computer Science, Dongshin University, Naju Jeonnam 58245, Korea)

  • Chang-Kyoon Son

    (Department of Applied Statistics, Dongguk University, Gyeongju Gyeongbuk 38066, Korea)

Abstract

In this paper, we extended Yennum et al.’s model, in which geometric distribution is used as a randomization device for a population that consists of different-sized clusters, and clusters are obtained by probability proportional to size (PPS) sampling. Estimators of a sensitive parameter, their variances, and their variance estimators are derived under PPS sampling and equal probability two-stage sampling, respectively. We also applied these sampling schemes to Yennum et al.’s generalized model. Numerical studies were carried out to compare the efficiencies of the proposed sampling methods for each case of Yennum et al.’s model and Yennum et al.’s generalized model.

Suggested Citation

  • Gi-Sung Lee & Ki-Hak Hong & Chang-Kyoon Son, 2019. "An Estimation of Sensitive Attribute Applying Geometric Distribution under Probability Proportional to Size Sampling," Mathematics, MDPI, vol. 7(11), pages 1-16, November.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:11:p:1102-:d:286937
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    References listed on IDEAS

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    1. Niharika Yennum & Stephen A. Sedory & Sarjinder Singh, 2019. "Improved strategy to collect sensitive data by using geometric distribution as a randomization device," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(23), pages 5777-5795, December.
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