Robustness properties of multivariate S-estimators

Unveiling the resilience and reliability in a multivariate statistical analysis

Bachelor Thesis (2023)
Author(s)

C. Marrone (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Hendrik P. Lopuhaa – Mentor (TU Delft - Statistics)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2023 Camillo Marrone
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Camillo Marrone
Graduation Date
17-07-2023
Awarding Institution
Delft University of Technology
Programme
['Applied Mathematics']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

This thesis investigates the robustness of multivariate S-estimators, which are statistical methods used to estimate the location and covariance parameters of multivariate distributions. Outliers, or atypical observations, can significantly impact statistical analyses, leading to incorrect conclusions. Robust methods, such as S-estimators, aim to reduce the influence of outliers, providing more reliable analysis results.
The primary objective is to assess the effectiveness of S-estimators through simulations using the statistical package R.

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