Robust Bayesian Analysis:
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
2000
|
| Schriftenreihe: | Lecture Notes in Statistics
152 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Robust Bayesian analysis aims at overcoming the traditional objection to Bayesian analysis of its dependence on subjective inputs, mainly the prior and the loss. Its purpose is the determination of the impact of the inputs to a Bayesian analysis (the prior, the loss and the model) on its output when the inputs range in certain classes. If the impact is considerable, there is sensitivity and we should attempt to further refine the information the incumbent classes available, perhaps through additional constraints on and/ or obtaining additional data; if the impact is not important, robustness holds and no further analysis and refinement would be required. Robust Bayesian analysis has been widely accepted by Bayesian statisticians; for a while it was even a main research topic in the field. However, to a great extent, their impact is yet to be seen in applied settings. This volume, therefore, presents an overview of the current state of robust Bayesian methods and their applications and identifies topics of further interest in the area. The papers in the volume are divided into nine parts covering the main aspects of the field. The first one provides an overview of Bayesian robustness at a non-technical level. The paper in Part II concerns foundational aspects and describes decision-theoretical axiomatisations leading to the robust Bayesian paradigm, motivating reasons for which robust analysis is practically unavoidable within Bayesian analysis |
| Beschreibung: | 1 Online-Ressource (XIII, 422p. 18 illus) |
| ISBN: | 9781461213062 9780387988665 |
| ISSN: | 0930-0325 |
| DOI: | 10.1007/978-1-4612-1306-2 |
Internformat
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Datensatz im Suchindex
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| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:05Z |
| institution | BVB |
| isbn | 9781461213062 9780387988665 |
| issn | 0930-0325 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027855214 |
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| spelling | Insua, David Ríos edt Robust Bayesian Analysis edited by David Ríos Insua, Fabrizio Ruggeri New York, NY Springer New York 2000 1 Online-Ressource (XIII, 422p. 18 illus) txt rdacontent c rdamedia cr rdacarrier Lecture Notes in Statistics 152 0930-0325 Robust Bayesian analysis aims at overcoming the traditional objection to Bayesian analysis of its dependence on subjective inputs, mainly the prior and the loss. Its purpose is the determination of the impact of the inputs to a Bayesian analysis (the prior, the loss and the model) on its output when the inputs range in certain classes. If the impact is considerable, there is sensitivity and we should attempt to further refine the information the incumbent classes available, perhaps through additional constraints on and/ or obtaining additional data; if the impact is not important, robustness holds and no further analysis and refinement would be required. Robust Bayesian analysis has been widely accepted by Bayesian statisticians; for a while it was even a main research topic in the field. However, to a great extent, their impact is yet to be seen in applied settings. This volume, therefore, presents an overview of the current state of robust Bayesian methods and their applications and identifies topics of further interest in the area. The papers in the volume are divided into nine parts covering the main aspects of the field. The first one provides an overview of Bayesian robustness at a non-technical level. The paper in Part II concerns foundational aspects and describes decision-theoretical axiomatisations leading to the robust Bayesian paradigm, motivating reasons for which robust analysis is practically unavoidable within Bayesian analysis Statistics Mathematical statistics Statistical Theory and Methods Statistik Bayes-Verfahren (DE-588)4204326-8 gnd rswk-swf Robuste Statistik (DE-588)4451047-0 gnd rswk-swf Bayes-Verfahren (DE-588)4204326-8 s Robuste Statistik (DE-588)4451047-0 s 1\p DE-604 Ruggeri, Fabrizio edt Lecture Notes in Statistics 152 (DE-604)BV036592911 152 https://doi.org/10.1007/978-1-4612-1306-2 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Robust Bayesian Analysis Lecture Notes in Statistics Statistics Mathematical statistics Statistical Theory and Methods Statistik Bayes-Verfahren (DE-588)4204326-8 gnd Robuste Statistik (DE-588)4451047-0 gnd |
| subject_GND | (DE-588)4204326-8 (DE-588)4451047-0 |
| title | Robust Bayesian Analysis |
| title_auth | Robust Bayesian Analysis |
| title_exact_search | Robust Bayesian Analysis |
| title_full | Robust Bayesian Analysis edited by David Ríos Insua, Fabrizio Ruggeri |
| title_fullStr | Robust Bayesian Analysis edited by David Ríos Insua, Fabrizio Ruggeri |
| title_full_unstemmed | Robust Bayesian Analysis edited by David Ríos Insua, Fabrizio Ruggeri |
| title_short | Robust Bayesian Analysis |
| title_sort | robust bayesian analysis |
| topic | Statistics Mathematical statistics Statistical Theory and Methods Statistik Bayes-Verfahren (DE-588)4204326-8 gnd Robuste Statistik (DE-588)4451047-0 gnd |
| topic_facet | Statistics Mathematical statistics Statistical Theory and Methods Statistik Bayes-Verfahren Robuste Statistik |
| url | https://doi.org/10.1007/978-1-4612-1306-2 |
| volume_link | (DE-604)BV036592911 |
| work_keys_str_mv | AT insuadavidrios robustbayesiananalysis AT ruggerifabrizio robustbayesiananalysis |