Hierarchical Modeling and Analysis for Spatial Data, Second Edition

Since the publication of the first edition, the statistical landscape has substantially changed for analyzing space and space-time data. More than twice the size of its predecessor, this second edition reflects the major growth in spatial statistics as both a research area and an area of application.

Duke statistical science professor Gelfand and his co-authors continue to provide a complete treatment of the theory, methods, and application of hierarchical modeling for spatial and spatiotemporal data. They tackle current challenges in handling this type of data, with increased emphasis on observational data, big data, and the upsurge of associated software tool while exploring important application domains, including environmental science, forestry, public health, and real estate.