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  • Search: subject:"High breakdown procedures"
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Year of publication
Subject
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Dimension reduction 3 High breakdown procedures 3 Outliers 3 Estimation theory 1 Regression analysis 1 Regressionsanalyse 1 Robust statistics 1 Robustes Verfahren 1 Schätztheorie 1
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Online availability
All
Free 3
Type of publication
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Book / Working Paper 3
Type of publication (narrower categories)
All
Working Paper 2 Arbeitspapier 1 Graue Literatur 1 Non-commercial literature 1
Language
All
English 2 Undetermined 1
Author
All
Becker, Claudia 3 Gather, Ursula 3 Hilker, Torsten 3
Institution
All
Institut für Wirtschafts- und Sozialstatistik, Universität Dortmund 1
Published in...
All
Technical Report 1 Technical Reports / Institut für Wirtschafts- und Sozialstatistik, Universität Dortmund 1 Technical report / Sonderforschungsbereich 475 Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 1
Source
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ECONIS (ZBW) 1 EconStor 1 RePEc 1
Showing 1 - 3 of 3
Cover Image
Robust sliced inverse regression procedures
Gather, Ursula; Hilker, Torsten; Becker, Claudia - 1998
Sliced Inverse Regression (SIR) is a promising technique for the purpose of dimension reduction. Several properties of this relatively new method have been examined already, but little attention has been paid to robustness aspects. We show that SIR is very sensitive towards outliers in the data....
Persistent link: https://www.econbiz.de/10010316531
Saved in:
Cover Image
Robust sliced inverse regression procedures
Gather, Ursula; Hilker, Torsten; Becker, Claudia - Institut für Wirtschafts- und Sozialstatistik, … - 1998
Sliced Inverse Regression (SIR) is a promising technique for the purpose of dimension reduction. Several properties of this relatively new method have been examined already, but little attention has been paid to robustness aspects. We show that SIR is very sensitive towards outliers in the data....
Persistent link: https://www.econbiz.de/10010955507
Saved in:
Cover Image
Robust sliced inverse regression procedures
Gather, Ursula; Hilker, Torsten; Becker, Claudia - 1998
Sliced Inverse Regression (SIR) is a promising technique for the purpose of dimension reduction. Several properties of this relatively new method have been examined already, but little attention has been paid to robustness aspects. We show that SIR is very sensitive towards outliers in the data....
Persistent link: https://www.econbiz.de/10010467714
Saved in:
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