Bayesian Method (English Version)

Author: Leonard (T.) et al. (USA)
Publisher:
Publish Date: 2005-01-01
Features: "This book provides important topics on modern Bayesian statistical methods, with fluent and elegant writing. Its outstanding features include a large number of practical applications, involving the use and comparison of AIC and BIC model selection criteria in several fields. It uniquely handles Bayesian decision theory through utility theory and discusses the frequentist properties of Bayesian processes, supplemented by interesting and moderate self-study exercises that can expand and deepen the content of the book." — Michael J. Evans, Mathematical Review "It introduces the basic principles of Bayesian modeling with rigorous, polished writing and thoughtfully selected material, introducing Bayesian methods at the graduate level." — Journal of the American Statistical Association
The "posterior distribution" or "predictive distribution" in Bayesian statistics is a summary of everything needed to understand unknown parameters or future observations. This book demonstrates, in a powerful and relevant way, how to apply Bayesian statistical techniques to draw conclusions about scientific, medical, and social issues from specific data. It explains the subtle assumptions required for Bayesian methodology and shows how to use these assumptions to obtain accurate results. The various methods introduced in this book are also very applicable to the frequentist properties of computer simulations. The book vividly outlines the Fisher method (frequentist method) while fully emphasizing likelihood, making it suitable as a textbook for mainstream statistics. It covers the progress of utility theory as well as time series and forecasting, making it also suitable for econometrics students. Additionally, the book includes topics such as linear models, categorical data analysis, survival and competitive analysis, random effects models, and nonlinear smoothing. The book provides numerous running examples, self-study exercises, and practical applications, making it suitable as a textbook for advanced undergraduate and graduate students, as well as for researchers in other interdisciplinary fields.