This book provides a comprehensive coverage of the fundamentals of Bayesian inference from all important perspectives, namely theory, methods and computations. All theoretical results are presented as formal theorems, corollaries, lemmas etc., furnished with detailed proofs.
This book provides a comprehensive coverage of the fundamentals of Bayesian inference from all important perspectives, namely theory, methods and computations. All theoretical results are presented as formal theorems, corollaries, lemmas etc., furnished with detailed proofs.
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.
Inhaltsangabe
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
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
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