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Outlier Identification Procedures for Contingency Tables using Maximum Likelihood and L1 Estimates

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  • Sonja Kuhnt

Abstract

. Observed cell counts in contingency tables are perceived as outliers if they have low probability under an anticipated loglinear Poisson model. New procedures for the identification of such outliers are derived using the classical maximum likelihood estimator and an estimator based on the L1 norm.

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  • Sonja Kuhnt, 2004. "Outlier Identification Procedures for Contingency Tables using Maximum Likelihood and L1 Estimates," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(3), pages 431-442, September.
    • Handle: RePEc:bla:scjsta:v:31:y:2004:i:3:p:431-442
    DOI: 10.1111/j.1467-9469.2004.02_057.x
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    Cited by:

    1. Mads Lindskou & Poul Svante Eriksen & Torben Tvedebrink, 2020. "Outlier detection in contingency tables using decomposable graphical models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(2), pages 347-360, June.
    2. Johan Koskinen & Peng Wang & Garry Robins & Philippa Pattison, 2018. "Outliers and Influential Observations in Exponential Random Graph Models," Psychometrika, Springer;The Psychometric Society, vol. 83(4), pages 809-830, December.

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