Multivariate outlier detection is usually based on Mahalanobis distances, by plugging in robust estimates of location and covariance. For compositional data, carrying only relative information, a special transformation needs to be consulted in order to be able to work in the appropriate geometry. The effect of the transformation is discussed in this contribution. Furthermore, different possibil...

I would like to congratulate M. Hubert, P. Rousseeuw and P. Segaert for this stimulating and useful work on outlier detection methods for multivariate functional data. They define and classify rigorously different types of functional outliers and propose several techniques for detecting them in multivariate functional data. These authors use the notion of data depth and distances derived from t...

This paper overviews and discusses our recent work on a multivariate conditional outlier detection framework for clinical applications.

In this paper, we consider one-step outlier identiication rules for multivariate data, generalizing the concept of so-called outlier identiiers, as presented in Davies and Gather (1993) for the case of univariate samples. We investigate, how the nite-sample breakdown points of estimators used in these identiication rules innuence the masking behaviour of the rules.

This study examines the liability of foreignness (LOF) faced by multinational enterprises (MNEs), and the effects of strategies employed to overcome the liability. Based on a sample of 3,085 Sino-foreign joint ventures formed in manufacturing sectors in China, the authors find that Hong Kong investors, who are often perceived to have lower LOF than investors from other countries, are more activ...

In this paper we consider one step outlier identi cation rules for multivariate data generalizing the concept of so called outlier identi ers as presented in Davies and Gather for the case of univariate samples We investigate how the nite sample breakdown points of estimators used in these identi cation rules in uence the masking behaviour of the rules

A fast and accurate technique has been developed for the determination of the total volatile content of rocks. The loss on fusion (LOF) results are comparable to the conventional time-consuming wet-chemical procedure but require no additional effort or cost when conducted as part of the usual sample preparation procedure for quantitative X-ray fluorescence spectrometric analysis (XRF). The tech...

A method for detecting outlier samples in a multivariate time series dataset is proposed. It assumed that an outlying characterized by having been generated from different process than those associated with the rest of series. Each described means estimator its quantile cross-spectral density, which treated as functional datum. Then score assigned to each using depths. broad simulation study sh...

Although various feature extraction algorithms have been developed for time series data, it is still challenging to obtain a flat vector representation with incorporating both of time-wise and variable-wise association between multiple series. Here we develop an algorithm, called Unsupervised Feature Extraction using Kernel Stacking (UFEKS), that constructs in unsupervised manner. UFEKS kernel ...