Edited by
Dipak Dey, University of Connecticut, CT, USA
C.R. Rao, The Pennsylvania State University, PA, USA
Description
This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application
point of view. It further describes parametric and nonparametric Bayesian methods for modelling and how to use modern computational methods
to summarize inferences using simulation. The book covers wide range of topics including objective and subjective Bayesian inferences
with a variety of applications in modelling categorical, survival, spatial, spatiotemporal, Epidemiological, software reliability, small
area and micro array data. The book concludes with a chapter on how to teach Bayesian thoughts to nonstatisticians.
Key Features:
- Critical thinking on causal effects
- Objective Bayesian philosophy
- Nonparametric Bayesian methodology
- Simulation
based computing techniques
- Bioinformatics and Biostatistics
Included in series
Handbook of Statistics
Audience:
Graduate students in Statistics, faculty and researchers interested in Bayesian philosophy and methodology, Scientists and Libraries.
