Socio-economic interrelationships among regions can be measured in terms of economic flows, migration, or physical geographically-based measures, such as distance or length of shared areal unit boundaries. In general, proximity and openness tend to favour a similar economic performance among...

Spatial interaction models of the gravity type are widely used to model origin-destination flows. They draw attention to three types of variables to explain variation in spatial interactions across geographic space: variables that characterize an origin region of a flow, variables that...

Socio-economic interrelationships among regions can be measured in terms of economic flows, migration, or physical geographically-based measures, such as distance or length of shared areal unit boundaries. In general, proximity and openness tend to favour a similar economic performance among...

The auto-Poisson model describes georeferenced data consisting of counts exhibiting spatial dependence. Its conventional specification is plagued by being restricted to only situations involving negative spatial autocorrelation, and an intractable normalizing constant. Work summarized here...

Data forming a short space-time series - too short to utilize a STARIMA model - can include a random effects term that is spatially structured in order to account for both serial and spatial autocorrelation. In this context, space-time heterogeneity can be accounted for in various ways,...

In the 1970s, spatial autocorrelation (i.e., local distance and configuration effects) and distance decay (i.e., global distance effects) were suspected of being intermingled in spatial interaction model specifications. This convolution was first treated in a theoretical context by Curry (1972),...

Regions, independent of their geographic level of aggregation, are known to be interrelated partly due to their relative locations. Similar economic performance among regions can be attributed to proximity. Consequently, a proper understanding, and accounting, of spatial liaisons is needed in...

The eigenfunction spatial filter derives from the Moran Coefficient that indexes spatial autocorrelation. Mean, variance and statistical distribution characterizations and descriptions of georeferenced random variables and their interrelationships are derived in terms of the eigenfunction...