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, 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. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Advancements in Bayesian Methods and Implementation INDICE: 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

• ISBN: 978-0-323-95268-2
• Editorial: Academic Press
• Encuadernacion: Cartoné
• Páginas: 420
• Fecha Publicación: 01/09/2022
• Nº Volúmenes: 1
• Idioma: Inglés