Introduction Probability Simulation Gibbs by Suess Eric (18 results)

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Paperback. Condition: very good. xiii, 307p, diagrams; 24 cm. Probabilities -- Simulation methods. R (Computer program language) Sampling (Statistics) Probabilities -- Simulation methods. R (Computer program language) Sampling (Statistics) Gibbs-sampling R Simulation Stichprobennahme Wahrscheinlichkeit Wahrscheinlichkeitsverteil…ung. Sparse hilites in yellow to approx 3-4 pages only; else tight clean and very good(++).

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Language: English
Published by Springer 2010-06 2010
Series: Use R!, Book 19 of 68. Book 19 of 68 - Use R!
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More imagesLanguage: English
Published by Springer New York 2010
Series: Use R!, Book 19 of 68. Book 19 of 68 - Use R!
- Softcover
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Taschenbuch. Condition: 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]c…om | Anbieter: preigu.

Language: English
Published by Springer New York 2010
Series: Use R!, Book 19 of 68. Book 19 of 68 - Use R!
- Softcover
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Taschenbuch. Condition: 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. Appl…ications 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.

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Language: English
Published by Springer-Verlag New York Inc. 2010
Series: Use R!, Book 19 of 68. Book 19 of 68 - Use R!
- Softcover
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Language: English
Published by Springer New York Jun 2010 2010
Series: Use R!, Book 19 of 68. Book 19 of 68 - Use R!
- Softcover
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Taschenbuch. Condition: 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 continu…ous 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.

Language: English
Published by Springer New York 2010
Series: Use R!, Book 19 of 68. Book 19 of 68 - Use R!
- Softcover
- Print on Demand
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Condition: 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.