An outlier nomination method based on the multihalver

This paper presents a method for detecting and nominating outliers based on the multihalver, or the delete-half jackknife. Since considering all possible half-samples is unpractical and unfeasable even for a moderate sample size, we present an algorithm for choosing a good set of half-samples. We also present an outlier detection method based on this algorithm. Simulations are given to show the effectiveness of our method and an example is also presented. © 2003 Elsevier B.V. All rights reserved.


Published in:
Journal of Statistical Planning and Inference, 122, 1-2, 125-139
Year:
2004
ISSN:
03783758
Laboratories:




 Record created 2012-11-06, last modified 2018-03-17


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