Monte Carlo Statistical Methods:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
1999
|
| Schriftenreihe: | Springer Texts in Statistics
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Monte Carlo statistical methods, particularly those based on Markov chains, have now matured to be part of the standard set of techniques used by statisticians. This book is intended to bring these techniques into the classroom, being (we hope) a self-contained logical development of the subject, with all concepts being explained in detail, and all theorems, etc. having detailed proofs. There is also an abundance of examples and problems, relating the concepts with statistical practice and enhancing primarily the application of simulation techniques to statistical problems of various difficulties. This is a textbook intended for a second-year graduate course. We do not assume that the reader has any familiarity with Monte Carlo techniques (such as random variable generation) or with any Markov chain theory. We do assume that the reader has had a first course in statistical theory at the level of Statistical Inference by Casella and Berger (1990). Unfortunately, a few times throughout the book a somewhat more advanced notion is needed. We have kept these incidents to a minimum and have posted warnings when they occur. While this is a book on simulation, whose actual implementation must be processed through a computer, no requirement is made on programming skills or computing abilities: algorithms are presented in a program-like format but in plain text rather than in a specific programming language. (Most of the examples in the book were actually implemented in C, with the S-Plus graphical interface |
| Beschreibung: | 1 Online-Ressource (XXI, 509 p) |
| ISBN: | 9781475730715 9781475730739 |
| ISSN: | 1431-875X |
| DOI: | 10.1007/978-1-4757-3071-5 |
Internformat
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| 245 | 1 | 0 | |a Monte Carlo Statistical Methods |c by Christian P. Robert, George Casella |
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| 500 | |a Monte Carlo statistical methods, particularly those based on Markov chains, have now matured to be part of the standard set of techniques used by statisticians. This book is intended to bring these techniques into the classroom, being (we hope) a self-contained logical development of the subject, with all concepts being explained in detail, and all theorems, etc. having detailed proofs. There is also an abundance of examples and problems, relating the concepts with statistical practice and enhancing primarily the application of simulation techniques to statistical problems of various difficulties. This is a textbook intended for a second-year graduate course. We do not assume that the reader has any familiarity with Monte Carlo techniques (such as random variable generation) or with any Markov chain theory. We do assume that the reader has had a first course in statistical theory at the level of Statistical Inference by Casella and Berger (1990). Unfortunately, a few times throughout the book a somewhat more advanced notion is needed. We have kept these incidents to a minimum and have posted warnings when they occur. While this is a book on simulation, whose actual implementation must be processed through a computer, no requirement is made on programming skills or computing abilities: algorithms are presented in a program-like format but in plain text rather than in a specific programming language. (Most of the examples in the book were actually implemented in C, with the S-Plus graphical interface | ||
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Datensatz im Suchindex
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| author | Robert, Christian P. |
| author_facet | Robert, Christian P. |
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| author_variant | c p r cp cpr |
| building | Verbundindex |
| bvnumber | BV042421413 |
| classification_tum | MAT 000 |
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| dewey-full | 519.5 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4757-3071-5 |
| format | Electronic eBook |
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| id | DE-604.BV042421413 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:08Z |
| institution | BVB |
| isbn | 9781475730715 9781475730739 |
| issn | 1431-875X |
| language | English |
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| spelling | Robert, Christian P. Verfasser aut Monte Carlo Statistical Methods by Christian P. Robert, George Casella New York, NY Springer New York 1999 1 Online-Ressource (XXI, 509 p) txt rdacontent c rdamedia cr rdacarrier Springer Texts in Statistics 1431-875X Monte Carlo statistical methods, particularly those based on Markov chains, have now matured to be part of the standard set of techniques used by statisticians. This book is intended to bring these techniques into the classroom, being (we hope) a self-contained logical development of the subject, with all concepts being explained in detail, and all theorems, etc. having detailed proofs. There is also an abundance of examples and problems, relating the concepts with statistical practice and enhancing primarily the application of simulation techniques to statistical problems of various difficulties. This is a textbook intended for a second-year graduate course. We do not assume that the reader has any familiarity with Monte Carlo techniques (such as random variable generation) or with any Markov chain theory. We do assume that the reader has had a first course in statistical theory at the level of Statistical Inference by Casella and Berger (1990). Unfortunately, a few times throughout the book a somewhat more advanced notion is needed. We have kept these incidents to a minimum and have posted warnings when they occur. While this is a book on simulation, whose actual implementation must be processed through a computer, no requirement is made on programming skills or computing abilities: algorithms are presented in a program-like format but in plain text rather than in a specific programming language. (Most of the examples in the book were actually implemented in C, with the S-Plus graphical interface Statistics Mathematical statistics Statistical Theory and Methods Statistik Markov-Kette (DE-588)4037612-6 gnd rswk-swf Monte-Carlo-Simulation (DE-588)4240945-7 gnd rswk-swf Monte-Carlo-Simulation (DE-588)4240945-7 s Markov-Kette (DE-588)4037612-6 s 1\p DE-604 Casella, George Sonstige oth https://doi.org/10.1007/978-1-4757-3071-5 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Robert, Christian P. Monte Carlo Statistical Methods Statistics Mathematical statistics Statistical Theory and Methods Statistik Markov-Kette (DE-588)4037612-6 gnd Monte-Carlo-Simulation (DE-588)4240945-7 gnd |
| subject_GND | (DE-588)4037612-6 (DE-588)4240945-7 |
| title | Monte Carlo Statistical Methods |
| title_auth | Monte Carlo Statistical Methods |
| title_exact_search | Monte Carlo Statistical Methods |
| title_full | Monte Carlo Statistical Methods by Christian P. Robert, George Casella |
| title_fullStr | Monte Carlo Statistical Methods by Christian P. Robert, George Casella |
| title_full_unstemmed | Monte Carlo Statistical Methods by Christian P. Robert, George Casella |
| title_short | Monte Carlo Statistical Methods |
| title_sort | monte carlo statistical methods |
| topic | Statistics Mathematical statistics Statistical Theory and Methods Statistik Markov-Kette (DE-588)4037612-6 gnd Monte-Carlo-Simulation (DE-588)4240945-7 gnd |
| topic_facet | Statistics Mathematical statistics Statistical Theory and Methods Statistik Markov-Kette Monte-Carlo-Simulation |
| url | https://doi.org/10.1007/978-1-4757-3071-5 |
| work_keys_str_mv | AT robertchristianp montecarlostatisticalmethods AT casellageorge montecarlostatisticalmethods |