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Identification of Outliers / by D. Hawkins
(Monographs on Statistics and Applied Probability)

版	1st ed. 1980.
出版者	(Dordrecht : Springer Netherlands : Imprint: Springer)
出版年	1980
本文言語	英語
大きさ	X, 188 p : online resource
著者標目	*Hawkins, D author SpringerLink (Online service)
件　名	LCSH:Social sciences LCSH:Humanities FREE:Humanities and Social Sciences
一般注記	1 Introduction -- 2 General theoretical principles -- 3 A single outlier in normal samples -- 4 The gamma distribution -- 5 Multiple outliers -- 6 Non-parametric tests -- 7 Outliers from the linear model -- 8 Multivariate outlier detection -- 9 Bayesian approach to outliers -- 10 Miscellaneous topics -- Appendix 5 Fractiles for testing for two outliers in normal data -- Appendix 6 Probabilities of the Mosteller test -- Appendix 7 Fractiles of the Doornbos test -- Appendix 8 Fractiles of the Wilks statistics -- Appendix 10 A single outlier in a two-way factorial experiment The problem of outliers is one of the oldest in statistics, and during the last century and a half interest in it has waxed and waned several times. Currently 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 need to bring them together in one place. That was the original intention of this monograph: but during execution it became clear that the existing theory of outliers was deficient in several areas, and so the monograph also contains a number of new results and conjectures. In view of the enormous volume ofliterature on the outlier problem and its cousins, no attempt has been made to make the coverage exhaustive. The material is concerned almost entirely 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 appeal or computational simplicity also are not discussed in any detail HTTP:URL=https://doi.org/10.1007/978-94-015-3994-4

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