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Best look-alike prediction: Another look at the Bayesian classifier and beyond

Author

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  • Sun, Hanmei
  • Jiang, Jiming
  • Nguyen, Thuan
  • Luan, Yihui

Abstract

A criterion of optimality in prediction is proposed that requires the predictor to assume the same type of values as the random variable it is predicting. In the case of categorical responses, the method leads to the Bayesian classifier with a uniform prior. However, the method extends to other cases, such as zero-inflated observations, as well. The method, called best look-alike prediction (BLAP), justifies an “usual practice” from a theoretical standpoint. Application of BLAP to small area estimation is considered. A real-data example is discussed.

Suggested Citation

  • Sun, Hanmei & Jiang, Jiming & Nguyen, Thuan & Luan, Yihui, 2018. "Best look-alike prediction: Another look at the Bayesian classifier and beyond," Statistics & Probability Letters, Elsevier, vol. 143(C), pages 37-42.
    • Handle: RePEc:eee:stapro:v:143:y:2018:i:c:p:37-42
    DOI: 10.1016/j.spl.2018.07.014
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    References listed on IDEAS

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    1. Datta, Gauri S. & Hall, Peter & Mandal, Abhyuday, 2011. "Model Selection by Testing for the Presence of Small-Area Effects, and Application to Area-Level Data," Journal of the American Statistical Association, American Statistical Association, vol. 106(493), pages 362-374.
    2. Jiming Jiang & P. Lahiri, 2006. "Mixed model prediction and small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(1), pages 1-96, June.
    3. Gauri Sankar Datta & Abhyuday Mandal, 2015. "Small Area Estimation With Uncertain Random Effects," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1735-1744, December.
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