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      • Computing and Mathematical Sciences
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      Shrinkage Estimation of Proportion via Logit Penalty

      Jung, Yoonsuh
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      Shrinkage Estimation of Proportion via Logit Penalty.pdf
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      DOI
       10.1080/03610926.2015.1048881
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      Jung, Y. (2016). Shrinkage Estimation of Proportion via Logit Penalty. Communications in Statistics - Theory and Methods. http://doi.org/10.1080/03610926.2015.1048881
      Permanent Research Commons link: https://hdl.handle.net/10289/10182
      Abstract
      By releasing the unbiasedness condition, we often obtain more accurate estimators due to the bias-variance tradeoff. In this paper, we propose a class of shrinkage proportion estimators which show improved performance over the sample proportion. We provide the “optimal” amount of shrinkage. The advantage of the proposed estimators is given theoretically as well as explored empirically by simulation studies and real data analyses.
      Date
      2016-04-05
      Type
      Journal Article
      Publisher
      Taylor & Francis
      Collections
      • Computing and Mathematical Sciences Papers [1454]
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