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Cover: 9780387922973 | Bayesian Computation with R | Jim Albert | Taschenbuch | Use R! | 2009
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Bayesian Computation with R
Taschenbuch von Jim Albert
Sprache: Englisch

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Beschreibung
There has been dramatic growth in the development and application of Bayesian inference in statistics. Berger (2000) documents the increase in Bayesian activity by the number of published research articles, the number of books,andtheextensivenumberofapplicationsofBayesianarticlesinapplied disciplines such as science and engineering. One reason for the dramatic growth in Bayesian modeling is the availab- ity of computational algorithms to compute the range of integrals that are necessary in a Bayesian posterior analysis. Due to the speed of modern c- puters, it is now possible to use the Bayesian paradigm to ?t very complex models that cannot be ?t by alternative frequentist methods. To ?t Bayesian models, one needs a statistical computing environment. This environment should be such that one can: write short scripts to de?ne a Bayesian model use or write functions to summarize a posterior distribution use functions to simulate from the posterior distribution construct graphs to illustrate the posterior inference An environment that meets these requirements is the R system. R provides a wide range of functions for data manipulation, calculation, and graphical d- plays. Moreover, it includes a well-developed, simple programming language that users can extend by adding new functions. Many such extensions of the language in the form of packages are easily downloadable from the Comp- hensive R Archive Network (CRAN).
There has been dramatic growth in the development and application of Bayesian inference in statistics. Berger (2000) documents the increase in Bayesian activity by the number of published research articles, the number of books,andtheextensivenumberofapplicationsofBayesianarticlesinapplied disciplines such as science and engineering. One reason for the dramatic growth in Bayesian modeling is the availab- ity of computational algorithms to compute the range of integrals that are necessary in a Bayesian posterior analysis. Due to the speed of modern c- puters, it is now possible to use the Bayesian paradigm to ?t very complex models that cannot be ?t by alternative frequentist methods. To ?t Bayesian models, one needs a statistical computing environment. This environment should be such that one can: write short scripts to de?ne a Bayesian model use or write functions to summarize a posterior distribution use functions to simulate from the posterior distribution construct graphs to illustrate the posterior inference An environment that meets these requirements is the R system. R provides a wide range of functions for data manipulation, calculation, and graphical d- plays. Moreover, it includes a well-developed, simple programming language that users can extend by adding new functions. Many such extensions of the language in the form of packages are easily downloadable from the Comp- hensive R Archive Network (CRAN).
Zusammenfassung

Introduces Bayesian modeling by use of computation using the R language

Includes supplementary material: [...]

Inhaltsverzeichnis
An Introduction to R.- to Bayesian Thinking.- Single-Parameter Models.- Multiparameter Models.- to Bayesian Computation.- Markov Chain Monte Carlo Methods.- Hierarchical Modeling.- Model Comparison.- Regression Models.- Gibbs Sampling.- Using R to Interface with WinBUGS.
Details
Erscheinungsjahr: 2009
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Reihe: Use R!
Inhalt: xii
300 S.
ISBN-13: 9780387922973
ISBN-10: 0387922970
Sprache: Englisch
Herstellernummer: 12537556
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Albert, Jim
Auflage: 2nd ed. 2009
Hersteller: Springer New York
Springer US, New York, N.Y.
Use R!
Maße: 235 x 155 x 17 mm
Von/Mit: Jim Albert
Erscheinungsdatum: 15.05.2009
Gewicht: 0,476 kg
Artikel-ID: 101576787
Zusammenfassung

Introduces Bayesian modeling by use of computation using the R language

Includes supplementary material: [...]

Inhaltsverzeichnis
An Introduction to R.- to Bayesian Thinking.- Single-Parameter Models.- Multiparameter Models.- to Bayesian Computation.- Markov Chain Monte Carlo Methods.- Hierarchical Modeling.- Model Comparison.- Regression Models.- Gibbs Sampling.- Using R to Interface with WinBUGS.
Details
Erscheinungsjahr: 2009
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Reihe: Use R!
Inhalt: xii
300 S.
ISBN-13: 9780387922973
ISBN-10: 0387922970
Sprache: Englisch
Herstellernummer: 12537556
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Albert, Jim
Auflage: 2nd ed. 2009
Hersteller: Springer New York
Springer US, New York, N.Y.
Use R!
Maße: 235 x 155 x 17 mm
Von/Mit: Jim Albert
Erscheinungsdatum: 15.05.2009
Gewicht: 0,476 kg
Artikel-ID: 101576787
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