Advancements in Bayesian Methods and Implementations
Advancements in Bayesian Methods and Implementation, Volume 47 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Fisher Information,...
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Advancements in Bayesian Methods and Implementation, Volume 47 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Fisher Information, Cramer-Rao and Bayesian Paradigm, Compound beta binomial distribution functions, MCMC for GLMMS, Signal Processing and Bayesian, Mathematical theory of Bayesian statistics where all models are wrong, Machine Learning and Bayesian, Non-parametric Bayes, Bayesian testing, and Data Analysis with humans, Variational inference or Functional horseshoe, Generalized Bayes.
Bibliographische Angaben
- Herausgegeben:Young, Alastair G; Srinivasa Rao, Arni S.R.; Rao, C. R.
- Verlag: Academic Press
- EAN: 9780323952682
Autoren-Porträt
Alastair Young works at Imperial College London, UKArni S.R. Srinivasa Rao works in pure mathematics, applied mathematics, probability, and artificial intelligence and applications in medicine. He is a Professor at the Medical College of Georgia, Augusta University, U.S.A, and the Director of the Laboratory for Theory and Mathematical Modeling housed within the Division of Infectious Diseases, Medical College of Georgia, Augusta, U.S.A. Previously, Dr. Rao conducted research and/or taught at Mathematical Institute, University of Oxford (2003, 2005-07), Indian Statistical Institute (1998-2002, 2006-2012), Indian Institute of Science (2002-04), University of Guelph (2004-06). Until 2012, Dr. Rao held a permanent faculty position at the Indian Statistical Institute. He has won the Heiwa-Nakajima Award (Japan) and Fast Track Young Scientists Fellowship in Mathematical Sciences (DST, New Delhi). Dr. Rao also proved a major theorem in stationary population models, such as, Rao's Partition Theorem in Populations, Rao-Carey Theorem in stationary populations, and developed mathematical modeling-based policies for the spread of diseases like HIV, H5N1, COVID-19, etc. He developed a new set of network models for understanding avian pathogen biology on grid graphs (these were called chicken walk models), AI Models for COVID-19 and received wide coverage in the science media. Recently, he developed concepts such as "Exact Deep Learning Machines?, and "Multilevel Contours? within a bundle of Complex Number Planes.
Inhaltsverzeichnis zu „Advancements in Bayesian Methods and Implementations “
1. Fisher Information, Cramer-Rao and Bayesian Paradigm Roy Frieden 2. Compound beta binomial distribution functions Angelo Plastino 3. MCMC for GLMMS Vivekananda Roy 4. Signal Processing and Bayesian Chandra Murthy 5. Mathematical theory of Bayesian statistics where all models are wrong Sumio Watanabe 6. Machine Learning and Bayesian Jun Zhu 7. Non-parametric Bayes Stephen Walker 8. Bayesian testing Christian Robert 9. Data Analysis with humans Sumio Kaski 10. Bayesian Inference under selection G. Alastair Young 10. Variational inference or Functional horseshoe Anirban Bhattacharya 11. Generalized Bayes Ryan Martin
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