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Monte Carlo Statistical Methods /
Until the advent of powerful and accessible computing methods, the experimenter was often confronted with a difficult choice. Either describe an accurate model of a phenomenon, which would usually preclude the computation of explicit answers, or choose a standard model which would allow this computa...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer New York,
1999.
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| Colección: | Springer texts in statistics.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Robert, Christian P. | |
| 245 | 1 | 0 | |a Monte Carlo Statistical Methods / |c by Christian P. Robert, George Casella. |
| 260 | |a New York, NY : |b Springer New York, |c 1999. | ||
| 300 | |a 1 online resource (xxi, 509 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 347 | |a text file | ||
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| 490 | 1 | |a Springer Texts in Statistics, |x 1431-875X | |
| 505 | 0 | |a Introduction -- Random Variable Generation -- Monte Carlo Integration -- Markov Chains -- Monte Carlo Optimization -- The Metropolis-Hastings Algorithm -- The Gibbs Sampler -- Diagnosing Convergence -- Implementation in Missing Data Models -- Probability Distributions -- Notation -- References -- Author Index -- Subject Index. | |
| 520 | |a Until the advent of powerful and accessible computing methods, the experimenter was often confronted with a difficult choice. Either describe an accurate model of a phenomenon, which would usually preclude the computation of explicit answers, or choose a standard model which would allow this computation, but may not be a close representation of a realistic model. This dilemma is present in many branches of statistical applications, for example in electrical engineering, aeronautics, biology, networks, and astronomy. Markov chain Monte Carlo methods have been developed to provide realistic models. | ||
| 546 | |a English. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Statistics. | |
| 650 | 0 | |a Mathematical statistics. | |
| 650 | 6 | |a Statistique. | |
| 650 | 7 | |a statistics. |2 aat | |
| 650 | 7 | |a Estadística matemática |2 embne | |
| 650 | 7 | |a Estadística |2 embne | |
| 650 | 7 | |a Mathematical statistics |2 fast | |
| 650 | 7 | |a Statistics |2 fast | |
| 700 | 1 | |a Casella, George. | |
| 758 | |i has work: |a Monte Carlo statistical methods (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGYRMryyyW637WQQgVr4Rq |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |z 9781475730739 |
| 830 | 0 | |a Springer texts in statistics. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=3085598 |z Texto completo |
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