Essential bayesian models
Dey, D. K.
Essential bayesian models - Amsterdam Elsevier 2011 - xii, 574 p. - A derivative of handbook of statistics: bayesian thinking - modeling and computation, Vol. 25 .
This accessible reference includes selected contributions from Bayesian Thinking - Modeling and Computation, Volume 25 in the Handbook of Statistics Series, with a focus on key methodologies and applications for Bayesian models and computation. It describes parametric and nonparametric Bayesian methods for modeling, and how to use modern computational methods to summarize inferences using simulation. The book covers a wide range of topics including objective and subjective Bayesian inferences, with a variety of applications in modeling categorical, survival, spatial, spatiotemporal, Epidemiological, small area and micro array data. (http://www.elsevier.com/wps/find/bookdescription.cws_home/724259/description#description)
9780444537324
Bayesian statistical decision theory
519.5 / E8
Essential bayesian models - Amsterdam Elsevier 2011 - xii, 574 p. - A derivative of handbook of statistics: bayesian thinking - modeling and computation, Vol. 25 .
This accessible reference includes selected contributions from Bayesian Thinking - Modeling and Computation, Volume 25 in the Handbook of Statistics Series, with a focus on key methodologies and applications for Bayesian models and computation. It describes parametric and nonparametric Bayesian methods for modeling, and how to use modern computational methods to summarize inferences using simulation. The book covers a wide range of topics including objective and subjective Bayesian inferences, with a variety of applications in modeling categorical, survival, spatial, spatiotemporal, Epidemiological, small area and micro array data. (http://www.elsevier.com/wps/find/bookdescription.cws_home/724259/description#description)
9780444537324
Bayesian statistical decision theory
519.5 / E8