Premium
REDUCED DISTANCE MEASURES AND TRANSFORMATIONS IN PROCESSING MULTIVARIATE OUTLIERS
Author(s) -
Barnett Vic
Publication year - 1983
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1983.tb01197.x
Subject(s) - outlier , multivariate statistics , multivariate normal distribution , multivariate analysis , sample (material) , class (philosophy) , computer science , statistics , econometrics , mathematics , artificial intelligence , chemistry , chromatography
Summary The study of multivariate outliers raises many problems of definition, principle and manipulation. Well‐authenticated tests of discordancy exist only for the multivariate normal distribution. Detection of outliers in non‐normal distributions involves the adoption of appropriate criteria to represent ‘extremeness' of observations in a sample; corresponding tests of discordancy usually require tedious, or even intractable, distributional and computational manipulations. A class of transformations of the data is considered with a view of transferring some of the familiar and desirable features of discordancy tests for normal samples to non‐normal situations.