Geographically weighted regression (GWR) is a way of exploring spatial nonstationarity by calibrating a multiple regression model which allows different relationships to exist at different points in space. Nevertheless, formal testing procedures for spatial nonstationarity have not been...

The entropy-maximixing model has been applied with varying degrees of success in the analysis and planning of origin - destination types of spatial interaction. Although theoretical underpinnings and solution methods have been developed over the years, there are still outstanding problems that...

In recent years, there has been a growing interest in the use of local measures such as Anselin's LISAs and Ord and Getis <i>G </i>statistics to identify local patterns of spatial association. The statistical significance test based on local statistics is one of the most important aspects in performing...

Geographically weighted regression (GWR) is a useful technique for exploring spatial nonstationarity by calibrating, for example, a regression model which allows different relationships to exist at different points in space. In this line of research, many spatial data sets have been successfully...