A hands-on introduction to the principles of Bayesian modeling
using WinBUGS"Bayesian Modeling Using WinBUGS" provides an easily
accessible introduction to the use of WinBUGS programming
techniques in a variety of Bayesian modeling settings. The author
provides an accessible treatment of the topic, offering readers a
smooth introduction to the principles of Bayesian modeling with
detailed guidance on the practical implementation of key
principles.The book begins with a basic introduction to Bayesian
inference and the WinBUGS software and goes on to cover key topics,
including: Markov Chain Monte Carlo algorithms in Bayesian
inferenceGeneralized linear modelsBayesian hierarchical
modelsPredictive distribution and model checkingBayesian model and
variable evaluationComputational notes and screen captures
illustrate the use of both WinBUGS as well as R software to apply
the discussed techniques. Exercises at the end of each chapter
allow readers to test their understanding of the presented concepts
and all data sets and code are available on the book's related Web
site.Requiring only a working knowledge of probability theory and
statistics, "Bayesian Modeling Using WinBUGS" serves as an
excellent book for courses on Bayesian statistics at the
upper-undergraduate and graduate levels. It is also a valuable
reference for researchers and practitioners in the fields of
statistics, actuarial science, medicine, and the social sciences
who use WinBUGS in their everyday work.
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!