eric suess (20 résultats)

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Taschenbuch. Etat : Neu. Introduction to Probability Simulation and Gibbs Sampling with R | Eric A Suess (u. a.) | Taschenbuch | xiii | Englisch | 2010 | Springer New York | EAN 9780387402734 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The first seven chapters use R for probability simulation and computation, including random number generation, numerical and Monte Carlo integration, and finding limiting distributions of Markov Chains with both discrete and continuous states. Applications include coverage probabilities of binomial confidence intervals, estimation of disease prevalence from screening tests, parallel redundancy for improved reliability of systems, and various kinds of genetic modeling. These initial chapters can be used for a non-Bayesian course in the simulation of applied probability models and Markov Chains. Chapters 8 through 10 give a brief introduction to Bayesian estimation and illustrate the use of Gibbs samplers to find posterior distributions and interval estimates, including some examples in which traditional methods do not give satisfactory results. WinBUGS software is introduced with a detailed explanation of its interface and examples of its use for Gibbs sampling for Bayesian estimation.No previous experience using R is required. An appendix introduces R, and complete R code is included for almost all computational examples and problems (along with comments and explanations). Noteworthy features of the book are its intuitive approach, presenting ideas with examples from biostatistics, reliability, and other fields; its large number of figures; and its extraordinarily large number of problems (about a third of the pages), ranging from simple drill to presentation of additional topics. Hints and answers are provided for many of the problems. These features make the book ideal for students of statistics at the senior undergraduate and at the beginning graduate levels.

Softcover. Etat : gut. Introduction to Probability Simulation and Gibbs Sampling with R (Use R!) In deutscher Sprache. pages.

189 S., 1 Bl. Mit sehr zahlr., meist farb. u. ganzs. Abb. Gr.-4°, Orig.-Pappbd. Eins von 850 nummerierten Exemplaren; im Druckvermerk vom Künstler signiert. - Einband minimalst berieben, sonst sehr gutes Exemplar. 1700 gr.

189 Seiten : Mit zahlreichen (teilweise farbigen) Abbildungen. Mit 6 Original Holzschnitten, diese signiert nummeriert und betitlelt vom Künstler Sehr guter Erhaltungszustand. Das Buch ist im Druckvermerk vom Künstler signiert. Sprache: Deutsch Gewicht in Gramm: 1700 Original-Leineneinband im Pappschuber. Dieses Werkverzeichnis erscheint in 850 nummerierten Exemplaren. Den Exemplaren 1-80 liegt eine Originalholzschnittmappe mit 6 Blättern bei. Dieses Exemplar trägt die Nummer: 40.

4° geb. Pappeinband. 189 S. Gebundener Pappeinband, 32 x 24 cm, keine nennenswerten Gebrauchsspuren, annähernd neuwertig, im Druckvermerk handschriftlich nummeriert (124) und von Klaus Süß signiert, zudem eine handschriftliche datierte Widmung mit Signatur an den Grafik-Sammler Karl Löffert und dessen Gattin Gerti. Umfangreiches Werkverzeichnis mit rund 100 ganzseitigen Farbabbildungen sowie rund 80 S. s/w-Werkverzeichnis mit jeweiligen Daten zu Auflage und Veröffentlichung. Suß2002 Sprache: Deutsch Gewicht in Gramm: 1400.

Etat : new. Questo è un articolo print on demand.

Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The first seven chapters use R for probability simulation and computation, including random number generation, numerical and Monte Carlo integration, and finding limiting distributions of Markov Chains with both discrete and continuous states. Applications include coverage probabilities of binomial confidence intervals, estimation of disease prevalence from screening tests, parallel redundancy for improved reliability of systems, and various kinds of genetic modeling. These initial chapters can be used for a non-Bayesian course in the simulation of applied probability models and Markov Chains. Chapters 8 through 10 give a brief introduction to Bayesian estimation and illustrate the use of Gibbs samplers to find posterior distributions and interval estimates, including some examples in which traditional methods do not give satisfactory results. WinBUGS software is introduced with a detailed explanation of its interface and examples of its use for Gibbs sampling for Bayesian estimation.No previous experience using R is required. An appendix introduces R, and complete R code is included for almost all computational examples and problems (along with comments and explanations). Noteworthy features of the book are its intuitive approach, presenting ideas with examples from biostatistics, reliability, and other fields; its large number of figures; and its extraordinarily large number of problems (about a third of the pages), ranging from simple drill to presentation of additional topics. Hints and answers are provided for many of the problems. These features make the book ideal for students of statistics at the senior undergraduate and at the beginning graduate levels. 307 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Probability simulation using R inlcuding the simulations of the Law of Large numbers and the Central Limit TheoremIntroduces the most common methods of Monte Carlo integration using R. Gibbs sampling introduced using R and WinBUGS to obtain interval estima.