Hierarchical Modeling and Analysis for Spatial Data

The 3rd edition of this popular and authoritative text on Bayesian modeling and inference for spatial and spatial-temporal data presents a comprehensive presents a comprehensive and up-to-date treatment of hierarchical and multilevel modeling for spatial and spatio-temporal data within a Bayesian framework.

Alan E. Gelfand is The James B Duke Professor Emeritus of Statistical Science at Duke University. He also enjoys a secondary appointment as Professor of Environmental Science and Policy in the Nicholas School. Author of more than 330 papers and 6 books, Gelfand is internationally known for his contributions to applied statistics, Bayesian computation and Bayesian inference. For the past thirty years, Gelfand’s primary research focus has been in the area of statistical modeling for spatial and space-time data. He has advanced methodology, using the Bayesian paradigm, to associate fully model-based inference with spatial and space-time data. His chief areas of application include spatio-temporal environmental and ecological processes.