2nd special issue on robust analysis of complex data. (English) Zbl 1464.00017

Comput. Stat. Data Anal. 113, 395-397 (2017).

From the text: When we embarked to invite submissions for this 2nd special issue on robust analysis of complex data, we did so with the following call:
Nowadays we are often confronted with large data sets in high dimensions. These new types of data have led to the emergence and use of complex models such as graphical models, models for complex correlation structures and models for functional data for instance. These complex structures pose many challenges. Specifically, when many measurements on several variables are recorded, it becomes more likely that not all of these measurements are recorded with high accuracy. This may result in data of uneven quality that contains gross errors and other anomalies that need to be taken into account. Therefore, there is a need for robust procedures that can reliably analyze large data sets containing outliers and other data contamination. This special issue will focus mainly on computationally efficient, robust procedures to analyze such complex data sets.
This call resulted in 37 submissions, from which five high quality papers have been selected for inclusion in this special issue. We greatly acknowledge the help of the CSDA co-editors to handle these papers and we thank all anonymous referees for their valuable comments, honest opinions and constructive suggestions.

MSC:

00B15	Collections of articles of miscellaneous specific interest
62-06	Proceedings, conferences, collections, etc. pertaining to statistics
62-08	Computational methods for problems pertaining to statistics

Software:

robNB

References:

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