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Can I read Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics) on EtoBox?

Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics) by Ming-Hui Chen, Qi-Man Shao, Joseph G. Ibrahim (auth.) is a mathematics available to read on EtoBox.

What is Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics) about?

Dealing with methods for sampling from posterior distributions and how to compute posterior quantities of interest using Markov chain Monte Carlo (MCMC) samples, this book addresses such topics as improving simulation accuracy, marginal posterior density estimation, estimation of normalizing constants, constrained parameter problems, highest posterior density interval calculations, computation of posterior modes, and posterior computations for proportional hazards models and Dirichlet process mo

Who reads Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics)?

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

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

Author
Ming-Hui Chen, Qi-Man Shao, Joseph G. Ibrahim (auth.)
Publisher
Springer-Verlag New York
Published
2000
Language
EN
ISBN
9780387989358
Category
mathematics
Subjects
Medical, Computer Science, Science
Updated
2026-03-25

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