Items related to Applied Bayesian Statistics: With R and OpenBUGS Examples
Synopsis
What is Bayesian statistics?.- Review of probability.- Introduction to one-parameter models.- Inference for a population proportion.- Special considerations in Bayesian inference.- Other one-parameter models and their conjugate priors.- More realism please: Introduction to multiparameter models.- Fitting more complex Bayesian models: Markov chain Monte Carlo.- Hierarchical models, and more on convergence assessment.- Regression and hierarchical regression models.- Model Comparison, Model Checking, and Hypothesis Testing.- References.- Index.
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About the Author
Kate Cowles taught Suzuki piano for many years before going to graduate school in Biostatistics. Her research areas are Bayesian and computational statistics, with application to environmental science. She is on the faculty of Statistics at The University of Iowa.
Review
From the book reviews:
“Tise textbook is based on the author’s course ‘Bayesian statistics’ and thus it is organised in an incremental manner that, using a variety of practical examples, guides the readers, students and researchers, through the concepts and methodologies required to perform Bayesian analysis. ... Each chapter contains examples that underline the important theoretical concepts that are presented and concludes with a selection of problems and exercises. ... this book is equally valuable to researchers and lecturers who wish to know more about Bayesian inference.” (Irina Ioana Mohorianu, zbMATH, Vol. 1276, 2014)
“This book ... provides a gentle introduction to both the theory and the ‘nuts and bolts’ of Bayesian analysis. ... For those (students in particular) who are looking for a friendly introduction to what is becoming a more popular statistical approach in many areas of science, Applied Bayesian Statistics: With R and OpenBUGS Examples is a very appropriate starting point, one that will give the reader enough understanding and experience to move on to more advanced treatments ... .” (Nicole Lazar, Technometrics, Vol. 55 (4), November, 2013)
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