Computational Bayesian Statistics

Discover the essential concepts of Bayesian analysis with Computational Bayesian Statistics by M. Antónia Amaral Turkman. Published by Cambridge University Press in 2019, this comprehensive guide spans 254 pages and delves into crucial computational methods, including MCMC and various software tools like R/R-INLA, OpenBUGS, JAGS, Stan, and BayesX.

Designed as both a textbook for graduate-level courses and a practical user’s guide, this book is perfect for researchers and graduate students venturing beyond traditional statistics. Whether you're looking to enhance your understanding of Bayesian statistical decision theory or seeking hands-on applications, this resource is invaluable for your academic journey. Elevate your statistical analysis skills with this insightful publication.