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Outlier detection in interval data
Publication . Silva, A. Pedro Duarte; Filzmoser, Peter; Brito, Paula
A multivariate outlier detection method for interval data is proposed that makes use of a parametric approach to model the interval data. The trimmed maximum likelihood principle is adapted in order to robustly estimate the model parameters. A simulation study demonstrates the usefulness of the robust estimates for outlier detection, and new diagnostic plots allow gaining deeper insight into the structure of real world interval data.

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Funding agency

Fundação para a Ciência e a Tecnologia

Funding programme

5876

Funding Award Number

UID/EEA/50014/2013

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