Bayesian Nonparametrics:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
2003
|
| Schriftenreihe: | Springer Series in Statistics
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Bayesian nonparametrics has grown tremendously in the last three decades, especially in the last few years. This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. While the book is of special interest to Bayesians, it will also appeal to statisticians in general because Bayesian nonparametrics offers a whole continuous spectrum of robust alternatives to purely parametric and purely nonparametric methods of classical statistics. The book is primarily aimed at graduate students and can be used as the text for a graduate course in Bayesian nonparametrics. Though the emphasis of the book is on nonparametrics, there is a substantial chapter on asymptotics of classical Bayesian parametric models. Jayanta Ghosh has been Director and Jawaharlal Nehru Professor at the Indian Statistical Institute and President of the International Statistical Institute. He is currently professor of statistics at Purdue University. He has been editor of Sankhya and served on the editorial boards of several journals including the Annals of Statistics. Apart from Bayesian analysis, his interests include asymptotics, stochastic modeling, high dimensional model selection, reliability and survival analysis and bioinformatics. R.V. Ramamoorthi is professor at the Department of Statistics and Probability at Michigan State University. He has published papers in the areas of sufficiency invariance, comparison of experiments, nonparametric survival analysis and Bayesian analysis. In addition to Bayesian nonparametrics, he is currently interested in Bayesian networks and graphical models. He is on the editorial board of Sankhya |
| Beschreibung: | 1 Online-Ressource (XII, 308 p) |
| ISBN: | 9780387226545 9780387955377 |
| ISSN: | 0172-7397 |
| DOI: | 10.1007/b97842 |
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Datensatz im Suchindex
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| author | Ghosh, J. K. |
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| dewey-ones | 519 - Probabilities and applied mathematics |
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| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/b97842 |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:04Z |
| institution | BVB |
| isbn | 9780387226545 9780387955377 |
| issn | 0172-7397 |
| language | English |
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| spelling | Ghosh, J. K. Verfasser aut Bayesian Nonparametrics by J. K. Ghosh, R. V. Ramamoorthi New York, NY Springer New York 2003 1 Online-Ressource (XII, 308 p) txt rdacontent c rdamedia cr rdacarrier Springer Series in Statistics 0172-7397 Bayesian nonparametrics has grown tremendously in the last three decades, especially in the last few years. This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. While the book is of special interest to Bayesians, it will also appeal to statisticians in general because Bayesian nonparametrics offers a whole continuous spectrum of robust alternatives to purely parametric and purely nonparametric methods of classical statistics. The book is primarily aimed at graduate students and can be used as the text for a graduate course in Bayesian nonparametrics. Though the emphasis of the book is on nonparametrics, there is a substantial chapter on asymptotics of classical Bayesian parametric models. Jayanta Ghosh has been Director and Jawaharlal Nehru Professor at the Indian Statistical Institute and President of the International Statistical Institute. He is currently professor of statistics at Purdue University. He has been editor of Sankhya and served on the editorial boards of several journals including the Annals of Statistics. Apart from Bayesian analysis, his interests include asymptotics, stochastic modeling, high dimensional model selection, reliability and survival analysis and bioinformatics. R.V. Ramamoorthi is professor at the Department of Statistics and Probability at Michigan State University. He has published papers in the areas of sufficiency invariance, comparison of experiments, nonparametric survival analysis and Bayesian analysis. In addition to Bayesian nonparametrics, he is currently interested in Bayesian networks and graphical models. He is on the editorial board of Sankhya Statistics Mathematical statistics Statistical Theory and Methods Statistik Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd rswk-swf Nichtparametrisches Verfahren (DE-588)4339273-8 gnd rswk-swf Bayes-Entscheidungstheorie (DE-588)4144220-9 s Nichtparametrisches Verfahren (DE-588)4339273-8 s 1\p DE-604 Ramamoorthi, R. V. Sonstige oth https://doi.org/10.1007/b97842 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Ghosh, J. K. Bayesian Nonparametrics Statistics Mathematical statistics Statistical Theory and Methods Statistik Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd Nichtparametrisches Verfahren (DE-588)4339273-8 gnd |
| subject_GND | (DE-588)4144220-9 (DE-588)4339273-8 |
| title | Bayesian Nonparametrics |
| title_auth | Bayesian Nonparametrics |
| title_exact_search | Bayesian Nonparametrics |
| title_full | Bayesian Nonparametrics by J. K. Ghosh, R. V. Ramamoorthi |
| title_fullStr | Bayesian Nonparametrics by J. K. Ghosh, R. V. Ramamoorthi |
| title_full_unstemmed | Bayesian Nonparametrics by J. K. Ghosh, R. V. Ramamoorthi |
| title_short | Bayesian Nonparametrics |
| title_sort | bayesian nonparametrics |
| topic | Statistics Mathematical statistics Statistical Theory and Methods Statistik Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd Nichtparametrisches Verfahren (DE-588)4339273-8 gnd |
| topic_facet | Statistics Mathematical statistics Statistical Theory and Methods Statistik Bayes-Entscheidungstheorie Nichtparametrisches Verfahren |
| url | https://doi.org/10.1007/b97842 |
| work_keys_str_mv | AT ghoshjk bayesiannonparametrics AT ramamoorthirv bayesiannonparametrics |