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Article

Cumulative Median Estimation for Sufficient Dimension Reduction

School of Mathematics, Cardiff University, Cardiff CF24 4AG, UK
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Academic Editor: Marco Riani
Received: 20 January 2021 / Revised: 12 February 2021 / Accepted: 14 February 2021 / Published: 20 February 2021
(This article belongs to the Special Issue Robust Statistics in Action)
In this paper, we present the Cumulative Median Estimation (CUMed) algorithm for robust sufficient dimension reduction. Compared with non-robust competitors, this algorithm performs better when there are outliers present in the data and comparably when outliers are not present. This is demonstrated in simulated and real data experiments. View Full-Text
Keywords: L1 median; regression; supervised dimension reduction L1 median; regression; supervised dimension reduction
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MDPI and ACS Style

Babos, S.; Artemiou, A. Cumulative Median Estimation for Sufficient Dimension Reduction. Stats 2021, 4, 138-145. https://0-doi-org.brum.beds.ac.uk/10.3390/stats4010011

AMA Style

Babos S, Artemiou A. Cumulative Median Estimation for Sufficient Dimension Reduction. Stats. 2021; 4(1):138-145. https://0-doi-org.brum.beds.ac.uk/10.3390/stats4010011

Chicago/Turabian Style

Babos, Stephen, and Andreas Artemiou. 2021. "Cumulative Median Estimation for Sufficient Dimension Reduction" Stats 4, no. 1: 138-145. https://0-doi-org.brum.beds.ac.uk/10.3390/stats4010011

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