Abstract
Ever since the first data sets have been collected and analyzed by specialists and scientists, the question of which observations are “normal” and which are not has been asked. There is a considerable amount of uncertainty and opacity in data analyses where authors claim that certain observations do not fit to the rest of the data and have therefore been removed or analyzed more accurately. However, no unique definition of the term “outlier” exists. Numerous proposals for this issue have been made. In this chapter we discuss the model-based concept of α-outliers, which predicates on the density of the assumed probability distribution.
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The financial support of the Deutsche Forschungsgemeinschaft (SFB 475, project A1 and SFB 823, project B1) is gratefully acknowledged.
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Kuhnt, S., Rehage, A. (2013). The Concept of α-Outliers in Structured Data Situations. In: Becker, C., Fried, R., Kuhnt, S. (eds) Robustness and Complex Data Structures. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35494-6_6
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DOI: https://doi.org/10.1007/978-3-642-35494-6_6
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