In recent years, there has been a renewed interest in applying statistical ranking criteria to
identify sites on a road network, which potentially present high traffic crash risks or are over …

Fast response and decision making about containment, management, eradication and
prevention of diseases, are increasingly important aspects of the work of public health …

Many theories in the social sciences predict spatial dependence or the similarity of
behaviors at neighboring locations. Spatial Analysis for the Social Sciences demonstrates …

Disease mapping involves the analysis of geo-referenced disease incidence data and has
many applications, for example within resource allocation, cluster alarm analysis, and …

In this paper, we provide critical reviews of methods suggested for the analysis of aggregate
count data in the context of disease mapping and spatial regression. We introduce a new …

The eruption of invasive wild pigs (IWP s) Sus scrofa throughout the world exemplifies the
need to understand the influences of exotic and nonnative species expansions. In particular …

Key features: Unique in its combination of serving as an introduction to spatial statistics and
to modeling agricultural and ecological data using R Provides exercises in each chapter to …

This study investigated the effects of including spatial heterogeneity in multivariate random
parameters models and their influence on different collision severity levels. The models …

An intermediate-level treatment of Bayesian hierarchical models and their applications, this
book demonstrates the advantages of a Bayesian approach to data sets involving inferences …

We investigated the spatial distribution, and social and economic correlates, of tuberculosis
in Brazil between 2002 and 2009 using municipality-level age/sex-standardized …