This paper reviews a number of conceptual issues pertaining to the implementation of an
explicit “spatial” perspective in applied econometrics. It provides an overview of the …

There is currently much interest in conducting spatial analyses of health outcomes at the
small-area scale. This requires sophisticated statistical techniques, usually involving …

Assembling a collection of very prominent researchers in the field, the Handbook of Spatial
Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects …

Among the many uses of hierarchical modeling, their application to the statistical analysis of
spatial and spatio-temporal data from areas such as epidemiology And environmental …

While mapped data provide a common ground for discussions between the public, the
media, regulatory agencies, and public health researchers, the analysis of spatially …

This new edition continues to serve as a comprehensive guide to modern and classical
methods of statistical computing. The book is comprised of four main parts spanning the …

Bayesian methods combine the evidence from the data at hand with previous quantitative
knowledge to analyse practical problems in a wide range of areas. The calculations were …

This paper proposes a unified framework for a Bayesian analysis of incidence or mortality
data in space and time. We introduce four different types of prior distributions for space× time …

and chapter 7 focuses on modeling of spatial distribution of diseases. Finally, chapter 8
explains data-driven and knowledge-driven modeling for risk assessment and management …

Spatial epidemiology is the description and analysis of the geographical distribution of
disease. It is more important now than ever, with modern threats such as bio-terrorism …