We present a novel inference methodology to perform Bayesian inference for spatiotemporal
Cox processes where the intensity function depends on a multivariate Gaussian process …

This paper analyses the effect of preferential sampling in Geostatistics when the choice of
new sampling locations is the main interest of the researcher. A Bayesian criterion based on …

The spatial distribution of surveillance-reported dengue cases and severity are usually
analyzed separately, assuming independence between the spatial distribution of non …

Population analyses of the correlates of neighborhood crime implicitly assume that a single
spatial unit can be used to assess neighborhood effects. However, no single spatial unit may …

Rich new marked point process data allow researchers to consider disparate problems such
as the factors affecting the location and type of police use of force incidents, and the …

In the last 30 years, a large number of studies have provided substantial statistical evidence
of the adverse health effects associated with air pollution. Statistical literature is very rich and …

A spatial point pattern is a set of event locations in 2D space or, for spatiotemporal events, in
3D space. Why would a social scientist be interested in event locations? A social scientist's …

The availability of large spatial data geocoded at accurate locations has fueled a growing
interest in spatial modeling and analysis of point processes. The proposed research is …

Point patterns are very common in present days of many researchers. The desire to
understand the spatial distribution and investigate connections between point patterns and p …

The availability of large-scale spatial and temporal data has fueled increasing interest in
statistical modelling and analysis. With the recent development of data collection and data …