Resistant estimates for high dimensional and functional data based on random projections
AbstractWe herein propose a new robust estimation method based on random projections that is adaptive and automatically produces a robust estimate, while enabling easy computations for high or infinite dimensional data. Under some restricted contamination models, the procedure is robust and attains full efficiency. We tested the method using both simulated and real data.
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Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 58 (2013)
Issue (Month): C ()
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Web page: http://www.elsevier.com/locate/csda
Robust estimates; Location and scatter estimates; Trimming estimates;
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