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Algorithms to compu...
Algorithms to compute CM - and S-estimates for regression
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- Arslan, O. (författare)
- Department of Mathematics, Cukurova University
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- Edlund, Ove (författare)
- Luleå tekniska universitet,Matematiska vetenskaper
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Ekblom, Håkan (författare)
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(creator_code:org_t)
- Physica-Verlag Rudolf Liebig GmbH, 2003
- 2003
- Engelska.
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Ingår i: International Conference on Robust Statistics. - : Physica-Verlag Rudolf Liebig GmbH. - 3790815187 ; , s. 62-76
- Relaterad länk:
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https://ltu.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Constrained M-estimators for regression were introduced by Mendes and Tyler in 1995 as an alternative class of robust regression estimators with high breakdown point and high asymptotic efficiency. To compute the CM-estimate, the global minimum of an objective function with an inequality constraint has to be localized. To find the S-estimate for the same problem, we instead restrict ourselves to the boundary of the feasible region. The algorithm presented for computing CM-estimates can easily be modified to compute S-estimates as well. Testing is carried out with a comparison to the algorithm SURREAL by Ruppert
Ämnesord
- NATURVETENSKAP -- Matematik -- Beräkningsmatematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Computational Mathematics (hsv//eng)
Nyckelord
- Scientific Computing
- Teknisk-vetenskapliga beräkningar
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