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Resistant outlier rules and the non-Gaussian case




The techniques of exploratory data analysis include a resistant rule, based on a linear combination of quartiles, for identification of outliers. This paper shows that the substitution of the quartiles with the median leads to a better performance in the non-Gaussian case. The improvement occurs in terms of resistance and efficiency, and an outside rate that is less affected by the sample size. The paper also studies issues of practical importance in the spirit of robustness by considering moderately skewed and fat tail distributions obtatined as special cases of the Generalized Lambda Distribution.

Suggested Citation

  • Carling, Kenneth, 1998. "Resistant outlier rules and the non-Gaussian case," Working Paper Series 2001:7, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  • Handle: RePEc:hhs:ifauwp:2001_007

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    More about this item


    Asymptotic efficiency; Generalized Lambda Distribution; Kurtosis; Outside rate; Resistance; Skewness; Small-sample bias;

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other


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