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Moderate-Deviation-Based Inference for Random Degeneration in Paired Rank Lists

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  • Peter Hall
  • Michael G. Schimek

Abstract

Consider a problem where N items (objects or individuals) are judged by assessors using their perceptions of a set of performance criteria, or alternatively by technical devices. In particular, two assessors might rank the items between 1 and N on the basis of relative performance, independently of each other. We can aggregate the rank lists by assigning one if the two assessors agree, and zero otherwise, and we can modify this approach to make it robust against irregularities. In this article, we consider methods and algorithms that can be used to address this problem. We study their theoretical properties in the case of a model based on nonstationary Bernoulli trials, and we report on their numerical properties for both simulated and real data.

Suggested Citation

  • Peter Hall & Michael G. Schimek, 2012. "Moderate-Deviation-Based Inference for Random Degeneration in Paired Rank Lists," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 661-672, June.
  • Handle: RePEc:taf:jnlasa:v:107:y:2012:i:498:p:661-672
    DOI: 10.1080/01621459.2012.682539
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    1. repec:bpj:sagmbi:v:16:y:2017:i:1:p:31-45:n:4 is not listed on IDEAS
    2. Li, Yumeng & Wang, Ran & Yao, Nian & Zhang, Shuguang, 2017. "A moderate deviation principle for stochastic Volterra equation," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 79-85.
    3. Arboretti, Rosa & Bonnini, Stefano & Corain, Livio & Salmaso, Luigi, 2014. "A permutation approach for ranking of multivariate populations," Journal of Multivariate Analysis, Elsevier, vol. 132(C), pages 39-57.
    4. repec:eee:csdana:v:115:y:2017:i:c:p:122-135 is not listed on IDEAS

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