"Introduction to Applied Bayesian Statistics and Estimation for Social Scientists" covers the complete process of Bayesian statistical analysis in great detail from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models t[...]

This book has been written for undergraduate and graduate students in various disciplines of mathematics. The authors, internationally recognized experts in their field, have developed a superior teaching and learning tool that makes it easy to grasp new concepts and apply them in practice. The book[...]

There has been a dramatic growth in the development and application of Bayesian inferential methods. Some of this growth is due to the availability of powerful simulation-based algorithms to summarize posterior distributions. There has been also a growing interest in the use of the system R for stat[...]

A self-contained introduction to probability, exchangeability and Bayes rule provides a theoretical understanding of the applied material. Numerous examples with R-code that can be run "as-is" allow the reader to perform the data analyses themselves. The development of Monte Carlo and Markov cha[...]

The second edition of this book includes revised, updated, and additional material on the structure, theory, and application of classes of dynamic models in Bayesian time series analysis and forecasting. In addition to wide ranging updates to central material, the second edition includes many more e[...]

The interest in Bayesian statistics among theoretical and applied statisticians has increased dramatically. This classic text and reference book remains one of the most important references.[...]

This volume provides the theories, methods and tools necessary for practical forecasting and analysis of time series.[...]

Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. This book provides an accessible introduction to Bayesian methods, tailored specifically for social science students. It [...]

Bayesian Statistical Modelling, Second Edition, provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets.[...]

There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. In Bayesian statistics the rules of probability are used to make inferences about the parameter. Prior information about the parameter an[...]