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Introduction To Probability Simulation And Gibbs Sampling With R (Cód: 2028418)

Eric A. Suess; Bruce E. Trumbo


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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.


Produto sob encomenda Sim
Cód. Barras 9780387402734
Altura 23.40 cm
I.S.B.N. 9780387402734
Profundidade 1.72 cm
Referência 9780387402734
Ano da edição 2010
Idioma Inglês
Número de Páginas 324
Peso 0.45 Kg
Largura 156.00 cm
AutorEric A. Suess; Bruce E. Trumbo


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