Resistant outlier rules and the non-Gaussian case.
type: Item
instance of: scholarly article
title: Resistant outlier rules and the non-Gaussian case.
zbMATH Open document ID: 1061.62502
DOI: 10.1016/S0167-9473(99)00057-2
published in: Computational Statistics and Data Analysis
publication date: 2000-08-21T00:00:00Z
review text: The techniques of exploratory data analysis include a resistant rule, based on a linear combination of quartiles, for the 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 improvment 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 obtained as special cases of the generalized lambda distribution.
Mathematics Subject Classification ID: 62-07
Mathematics Subject Classification ID: 62F35
zbMATH DE Number: 1493180
zbMATH Keywords: Asymptotic efficiency
zbMATH Keywords: Generalized lambda distribution
zbMATH Keywords: Kurtosis
zbMATH Keywords: Outside rate
zbMATH Keywords: Resistance
zbMATH Keywords: Skewness
zbMATH Keywords: Small-sample bias
author: Kenneth Carling
MaRDI profile type: Publication
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Wikidata QID: Q126778840
full work available at URL: s0167-9473(99)00057-2
OpenAlex ID: W2134518716
description: scientific article; zbMATH DE number 1493180