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Introduction to Probability Simulation and Gibbs Sampling with R (Paperback, 2010 ed.)
Loot Price: R2,726
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Introduction to Probability Simulation and Gibbs Sampling with R (Paperback, 2010 ed.)
Series: Use R!
Expected to ship within 10 - 15 working days
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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.
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