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- W2328769048 abstract "A new technique called the generalized gap test for the detection of multivariate outliers is presented. It is based on the observation that the distribution of the lengths of the edges of minimum spanning trees (based on a matrix of distances between all pairs of points) is quite sensitive to the presernce of observations separated from the main mtultivariate cloud of points. If the data are multivariate normal then the distribution of squared edge lengths follows the gamma distribution quite closely. Thus departure from expectation can be detected using gamma quantile plots. A table of critical values is also given for testing whether the maximum squared edge length divided by the mean squared edge length is too large." @default.
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- W2328769048 title "Generalization of the Gap Test for the Detection of Multivariate Outliers" @default.
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- W2328769048 doi "https://doi.org/10.2307/2529711" @default.
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