On Rohlf′s Method for the Detection of Outliers in Multivariate Data

 
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Journal part (EN)
Scientific article (EN)
1995 (EN)
On Rohlf′s Method for the Detection of Outliers in Multivariate Data (EN)
Caroni, C (EN)
Prescott, P (EN)
Rohlf (1975, Biometrics31, 93-101) proposed a method of detecting outliers in multivariate data by testing the largest edge of the minimum spanning tree. It is shown here that tests against the gamma distribution are extremely liberal. Furthermore, results depend on the correlation structure of the data if Euclidean distances are used. While the use of generalized distances might avoid this difficulty, the construction of the robust estimates required to carry out the test with generalized distances provides in itself information on outliers which leaves Rohlf′s procedure superfluous. It is concluded that Rohlf′s method does not provide a useful formal test. © 1995 Academic Press. All rights reserved. (EN)
journalArticle (EN)
ROHLFS TEST (EN)
GAMMA DISTRIBUTION (EN)
Statistics & Probability (EN)
MULTIVARIATE OUTLIERS (EN)
GAP TESTS (EN)
OUTLIER TESTS (EN)
POINTS (EN)
MULTIPLE OUTLIERS (EN)
National Technical University of Athens
Digital Library of National Technical University of Athens | Dspace@NTUA
Κεντρική Βιβλιοθήκη Ε.Μ.Π.
Ιδρυματικό Αποθετήριο
Δημοσιεύσεις μελών Δ.Ε.Π. σε περιοδικά
Journal of Multivariate Analysis (EN)
English
1995 (EN)
http://hdl.handle.net/123456789/11599
0047-259X (EN)
2 (EN)
307 (EN)
10.1006/jmva.1995.1015 (EN)
52 (EN)
ISI:A1995QH97600006 (EN)
295 (EN)
ACADEMIC PRESS INC JNL-COMP SUBSCRIPTIONS (EN)



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