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Can I read Understanding Computational Bayesian Statistics (Wiley Series in Computational Statistics) on EtoBox?

Understanding Computational Bayesian Statistics (Wiley Series in Computational Statistics) by William M Bolstad, 1943- is a nonfiction available to read on EtoBox.

What is Understanding Computational Bayesian Statistics (Wiley Series in Computational Statistics) about?

A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistical models, including the multiple linear regression model, the hierarchical mean model, the logistic regression model, and the proportional hazards model. The book begins with an outline of the similarities and differences between Bayesian and the likelihood approaches to statistics. Subsequent chapters present key techniques for using computer software to draw Monte Carlo samples from the incompletely known posterior distribution and performing the Bayesian inference calculated from these samples. Topics of coverage include: Direct ways to draw a random sample from the posterior by reshaping

Who reads Understanding Computational Bayesian Statistics (Wiley Series in Computational Statistics)?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
William M Bolstad, 1943-
Publisher
Wiley & Sons, Incorporated, John
Published
2009
Language
EN
ISBN
9780470567340
Category
nonfiction
Subjects
Mathematics, Stem

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