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A New Graphical Method for Detecting Single and Multiple Outliers in Univariate and Multivariate Data
Author(s) -
BaconShone J.,
Fung W. K.
Publication year - 1987
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2347547
Subject(s) - univariate , multivariate statistics , outlier , multivariate analysis , computer science , statistics , data mining , artificial intelligence , mathematics
SUMMARY A new graphical approach based on Wilks's (1963) statistic is proposed. The method is found to be useful in the detection of outliers in univariate and multivariate data. Masking and swamping effects in the sample are easily revealed. The method is illustrated with examples and simulations.