Robust statistical procedures:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Philadelphia, Pa.
Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104)
1996
|
| Ausgabe: | 2nd ed |
| Schriftenreihe: | CBMS-NSF regional conference series in applied mathematics
68 |
| Schlagworte: | |
| Online-Zugang: | TUM01 UBW01 UBY01 UER01 Volltext |
| Beschreibung: | Mode of access: World Wide Web. - System requirements: Adobe Acrobat Reader Includes bibliographical references (s. 65-67) Preface to the Second Edition -- Preface to the First Edition -- Chapter 1. Background. Why robust procedures? -- Chapter 2. Qualitative and quantitative robustness. Qualitative robustness; Quantitative robustness, breakdown; Infinitesimal robustness, influence function -- Chapter 3. M-,L-, and R-estimates. M-estimates; L-estimates; R-estimates; Asymptotic properties of M-estimates; Asymptotically efficient M-, L-, R-estimates; Scaling question -- Chapter 4. Asymptotic Minimax theory. Minimax asymptotic bias; Minimax asymptotic variance -- Chapter 5. Multiparameter problems. Generalities; Regression; Robust covariances: the affinely invariant case; Robust covariances: the coordinate dependent case -- Chapter 6. Finite sample Minimax theory. Robust tests and capacities; Finite sample minimax estimation -- Chapter 7. Adaptive estimates. Adaptive estimates -- Chapter 8. Robustness: Where are we now? The first ten years; Influence functions and psuedovalues; Breakdown and outlier detection; Studentizing; Shrinking neighborhoods; Design; Regression; Multivariate problems; Some persistent misunderstandings; Future directions -- References Here is a brief, well-organized, and easy-to-follow introduction and overview of robust statistics. Huber focuses primarily on the important and clearly understood case of distribution robustness, where the shape of the true underlying distribution deviates slightly from the assumed model (usually the Gaussian law). An additional chapter on recent developments in robustness has been added and the reference list has been expanded and updated from the 1977 edition |
| Beschreibung: | 1 Online-Ressource (ix, 67 Seiten) |
| ISBN: | 089871379X 9780898713794 |
| DOI: | 10.1137/1.9781611970036 |
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| 500 | |a Includes bibliographical references (s. 65-67) | ||
| 500 | |a Preface to the Second Edition -- Preface to the First Edition -- Chapter 1. Background. Why robust procedures? -- Chapter 2. Qualitative and quantitative robustness. Qualitative robustness; Quantitative robustness, breakdown; Infinitesimal robustness, influence function -- Chapter 3. M-,L-, and R-estimates. M-estimates; L-estimates; R-estimates; Asymptotic properties of M-estimates; Asymptotically efficient M-, L-, R-estimates; Scaling question -- Chapter 4. Asymptotic Minimax theory. Minimax asymptotic bias; Minimax asymptotic variance -- Chapter 5. Multiparameter problems. Generalities; Regression; Robust covariances: the affinely invariant case; Robust covariances: the coordinate dependent case -- Chapter 6. Finite sample Minimax theory. Robust tests and capacities; Finite sample minimax estimation -- Chapter 7. Adaptive estimates. Adaptive estimates -- Chapter 8. Robustness: Where are we now? The first ten years; Influence functions and psuedovalues; Breakdown and outlier detection; Studentizing; Shrinking neighborhoods; Design; Regression; Multivariate problems; Some persistent misunderstandings; Future directions -- References | ||
| 500 | |a Here is a brief, well-organized, and easy-to-follow introduction and overview of robust statistics. Huber focuses primarily on the important and clearly understood case of distribution robustness, where the shape of the true underlying distribution deviates slightly from the assumed model (usually the Gaussian law). An additional chapter on recent developments in robustness has been added and the reference list has been expanded and updated from the 1977 edition | ||
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Datensatz im Suchindex
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| author | Huber, Peter J. 1934- |
| author_GND | (DE-588)112055745 |
| author_facet | Huber, Peter J. 1934- |
| author_role | aut |
| author_sort | Huber, Peter J. 1934- |
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| discipline | Mathematik Wirtschaftswissenschaften |
| doi_str_mv | 10.1137/1.9781611970036 |
| edition | 2nd ed |
| format | Electronic eBook |
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| spelling | Huber, Peter J. 1934- Verfasser (DE-588)112055745 aut Robust statistical procedures Peter J. Huber 2nd ed Philadelphia, Pa. Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104) 1996 1 Online-Ressource (ix, 67 Seiten) txt rdacontent c rdamedia cr rdacarrier CBMS-NSF regional conference series in applied mathematics 68 Mode of access: World Wide Web. - System requirements: Adobe Acrobat Reader Includes bibliographical references (s. 65-67) Preface to the Second Edition -- Preface to the First Edition -- Chapter 1. Background. Why robust procedures? -- Chapter 2. Qualitative and quantitative robustness. Qualitative robustness; Quantitative robustness, breakdown; Infinitesimal robustness, influence function -- Chapter 3. M-,L-, and R-estimates. M-estimates; L-estimates; R-estimates; Asymptotic properties of M-estimates; Asymptotically efficient M-, L-, R-estimates; Scaling question -- Chapter 4. Asymptotic Minimax theory. Minimax asymptotic bias; Minimax asymptotic variance -- Chapter 5. Multiparameter problems. Generalities; Regression; Robust covariances: the affinely invariant case; Robust covariances: the coordinate dependent case -- Chapter 6. Finite sample Minimax theory. Robust tests and capacities; Finite sample minimax estimation -- Chapter 7. Adaptive estimates. Adaptive estimates -- Chapter 8. Robustness: Where are we now? The first ten years; Influence functions and psuedovalues; Breakdown and outlier detection; Studentizing; Shrinking neighborhoods; Design; Regression; Multivariate problems; Some persistent misunderstandings; Future directions -- References Here is a brief, well-organized, and easy-to-follow introduction and overview of robust statistics. Huber focuses primarily on the important and clearly understood case of distribution robustness, where the shape of the true underlying distribution deviates slightly from the assumed model (usually the Gaussian law). An additional chapter on recent developments in robustness has been added and the reference list has been expanded and updated from the 1977 edition Robust statistics Distribution (Probability theory) Schätztheorie (DE-588)4121608-8 gnd rswk-swf Robuste Statistik (DE-588)4451047-0 gnd rswk-swf 1\p (DE-588)1071861417 Konferenzschrift gnd-content Robuste Statistik (DE-588)4451047-0 s DE-604 Schätztheorie (DE-588)4121608-8 s 2\p DE-604 Erscheint auch als Druck-Ausgabe, Paperback 089871379X Erscheint auch als Druck-Ausgabe, Paperback 9780898713794 CBMS-NSF regional conference series in applied mathematics 68 (DE-604)BV046682627 68 https://doi.org/10.1137/1.9781611970036 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Huber, Peter J. 1934- Robust statistical procedures CBMS-NSF regional conference series in applied mathematics Robust statistics Distribution (Probability theory) Schätztheorie (DE-588)4121608-8 gnd Robuste Statistik (DE-588)4451047-0 gnd |
| subject_GND | (DE-588)4121608-8 (DE-588)4451047-0 (DE-588)1071861417 |
| title | Robust statistical procedures |
| title_auth | Robust statistical procedures |
| title_exact_search | Robust statistical procedures |
| title_full | Robust statistical procedures Peter J. Huber |
| title_fullStr | Robust statistical procedures Peter J. Huber |
| title_full_unstemmed | Robust statistical procedures Peter J. Huber |
| title_short | Robust statistical procedures |
| title_sort | robust statistical procedures |
| topic | Robust statistics Distribution (Probability theory) Schätztheorie (DE-588)4121608-8 gnd Robuste Statistik (DE-588)4451047-0 gnd |
| topic_facet | Robust statistics Distribution (Probability theory) Schätztheorie Robuste Statistik Konferenzschrift |
| url | https://doi.org/10.1137/1.9781611970036 |
| volume_link | (DE-604)BV046682627 |
| work_keys_str_mv | AT huberpeterj robuststatisticalprocedures |