1st Edition
Bayesian Inference Theory, Methods, Computations
1. Introduction
2. Bayesian Modelling
3. Choice of Prior
4. Decision Theory
5. Asymptotic Theory
6. Normal Linear Models
7. Estimation
8. Testing and Model Comparison
9. Computational Techniques
10. Solutions
11. Appendix
Index
Biography
Silvelyn Zwanzig is a Professor for Mathematical Statistics at Uppsala University. She studied Mathematics at the Humboldt University in Berlin. Before coming to Sweden, she was Assistant Professor at the University of Hamburg in Germany. She received her Ph.D. in Mathematics at the Academy of Sciences of the GDR. She has taught Statistics to undergraduate and graduate students since 1991. Her research interests include theoretical statistics and computer-intensive methods.
Rauf Ahmad is Associate Professor at the Department of Statistics, Uppsala University. He did his Ph.D. at Göttingen University, Germany. Before joining Uppsala University, he worked at the Division of Mathematical Statistics, Department of Mathematics, Linköping University, and at Biometry Division, Swedish University of Agricultural Sciences, Uppsala. He has taught Statistics to undergraduate and graduate students since 1995. His research interests include high-dimensional inference, mathematical statistics, and U-statistics.
"One of the distinguishing features of this textbook is its emphasis on recent Bayesian computational techniques, particularly in Chapter 9. Each computational method is accompanied by clear explanations, pseudocode, algorithms, and practical examples. The book also includes implementations in R,enabling readers to bridge the gap between theory and practice.This computational focus makes the book particularly useful for data scientists and applied researchers who need efficient Bayesian inference techniques for real-world problems."
-Kazuhiko Kakamu and Shuangzhe Liu, Technometrics 67 (4): 728–29, 2025.
