BOOK
Bayesian Statistical Modelling
Bayesian Statistical Modelling provides a comprehensive introduction to the theory and practice of Bayesian inference, particularly as applied to hierarchical and complex models. Peter Congdon presents a wide array of real-world applications using Bayesian methods, emphasizing computational techniques such as Markov Chain Monte Carlo (MCMC). The book is well-suited for statisticians and researchers in the social, health, and environmental sciences who need to model data structures involving random effects, latent variables, and spatial or time series dependencies.
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