Abstract
The goal of robust statistics is to develop methods that are robust against outliers in the data. We emphasize on high breakdown estimators, which can deal with heavy contamination in the data set. We give an overview of recent popular robust methods and present our new approach using operational research techniques, like mathematical programming. We present some open problems of the new robust procedures for improving robustness and efficiency of the proposed estimators.
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Zioutas, G., Chatzinakos, C., Migdalas, A. (2018). New Statistical Robust Estimators, Open Problems. In: Pardalos, P., Migdalas, A. (eds) Open Problems in Optimization and Data Analysis. Springer Optimization and Its Applications, vol 141. Springer, Cham. https://doi.org/10.1007/978-3-319-99142-9_3
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DOI: https://doi.org/10.1007/978-3-319-99142-9_3
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