Resistant outlier rules and the non-Gaussian case
AbstractThe 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by IFAU - Institute for Evaluation of Labour Market and Education Policy in its series Working Paper Series with number 2001:7.
Length: 14 pages
Date of creation: 01 Sep 1998
Date of revision:
Publication status: Published in Computational Statistics and Data Analysis, 2000, pages 249-258.
Asymptotic efficiency; Generalized Lambda Distribution; Kurtosis; Outside rate; Resistance; Skewness; Small-sample bias;
Find related papers by JEL classification:
- C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Margareta Wicklander).
If references are entirely missing, you can add them using this form.