Titlebook: Identification of Outliers; D. M. Hawkins Book 1980 D. M. Hawkins 1980 Area.Factor.Flit.Volume.computation.distribution.identification.sta

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A single outlier in normal samples,A later chapter will relax this assumption of identical distribution by assuming that the data are generated by a homoscedastic general linear model. It will also be assumed that, if the null hypothesis is false, at most a single outlier is present. This assumption will also be relaxed in a later chapter.

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Multivariate outlier detection,. . , . such that . while .. . . . , .. follow some other distribution or distributions. It is convenient, and seems not to result in much loss of generality, to suppose that the outliers also follow multivariate normal distributions, but with at least one parameter different from (., .).

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Book 1980urrently it is once again an active research area after some years of relative neglect, and recent work has solved a number of old problems in outlier theory, and identified new ones. The major results are, however, scattered amongst many journal articles, and for some time there has been a clear ne

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Book 1980tirely with the use of outlier tests that are known (or may reasonably be expected) to be optimal in some way. Such topics as robust estimation are largely ignored, being covered more adequately in other sources. The numerous ad hoc statistics proposed in the early work on the grounds of intuitive a

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