, statistical theory is now mostly available (Simar and Wilson, 2000a). In the presence of super-efficient outliers, envelopment …. (2002) on robust nonparametric frontier estimators may be used in order to detect outliers by defining a new DEA …, we summarize the main results of Cazals et al. (2002) and we show how this tool can be used for detecting outliers when …

as the choice of the smoother. Especially, when outliers are present, robust cross-validation criteria are needed. So far …. These combinations are compared in a simulation study under a broad variety of data situations with outliers and abrupt … case of large percentages of outliers and the Tukey-criterion in case of data situations with jumps, even if the data are …

multivariate outliers. Copyright Springer-Verlag Berlin Heidelberg 2014 …

, which is intended for outliers. The model is proposed as an alternative to the search for the order of a single …

the data generating processes, we find that outliers distort the size of the test and that the distortion increases with … the level of persistence. However, contrary to what one might expect, we also find that larger outliers could help improve …

]. The definition of outliers is subject to analysis and interpretation of results. Decisions regarding the identification of … outliers should be taken individually and depend on a specific experiment [1]. Control charts are records of observations in … of statistical control and the value identified is defined as an outlier. Thus, this work aims at identifying outliers by …