Extreme Value Theory Filtering Techniques for Outlier Detection

Olmo, J. (2009). Extreme Value Theory Filtering Techniques for Outlier Detection (Report No. 09/09). London, UK: Department of Economics, City University London.

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Abstract

We introduce asymptotic parameter-free hypothesis tests based on extreme value theory to detect outlying observations in finite samples. Our tests have nontrivial power for detecting outliers for general forms of the parent distribution and can be implemented when this is unknown and needs to be estimated. Using these techniques this article also develops an algorithm to uncover outliers masked by the presence of influential observations.

Item Type: Monograph (Discussion Paper)
Additional Information: © 2009 the author
Uncontrolled Keywords: Extreme value theory, Hypothesis tests, Outlier detection, Power function, Robust estimation
Subjects: H Social Sciences > HB Economic Theory
Divisions: School of Social Sciences > Department of Economics > Department of Economics Discussion Paper Series
URI: http://openaccess.city.ac.uk/id/eprint/1581

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