The technique of geographically weighted regression (GWR) is used to model spatial ‘drift’ in linear model coefficients. In this paper we extend the ideas of GWR in a number of ways. First, we introduce a set of analytically derived significance tests allowing a null hypothesis of no spatial parameter drift to be investigated. Second, we discuss ‘mixed’ GWR models where some parameters are fixe...

SUMMARY The primary objective of this study was to assess a human-induced dryland degradation in the cachment basin of the Balkhash Lake in the Middle Kazakhstan based on time series of rainfall data and normalized difference vegetation index (NDVI) for the period 1985-2000. We developed a method to remove the climatic signal from the change in vegetation activity over the study period. By appl...

Although relationships between fragmentation of urban development and other forms of administrative and land cover fragmentation are important, they are poorly understood. This research aimed to better understand these relationships in order to inform land use planning in the Roaring Fork/Colorado River Corridor of Colorado. Change in fragmentation of urban development between 1985 and 1999 was...

Despite the growing ubiquity of sensor deployments and the advances in sensor data analysis technology, relatively little attention has been paid to the spatial non-stationarity of sensed data which is an intrinsic property of the geographically distributed data. In this paper we deal with non-stationarity of geographically distributed data for the task of regression. At this purpose, we extend...

The effective use of spatial information, that is the geographic locations of population units, in a regression model-based approach to small area estimation is an important practical issue. One approach for incorporating such spatial information in a small area regression model is via Geographically Weighted Regression (GWR). In GWR the relationship between the outcome variable and the covaria...

Fine particulate matter (PM2.5) is an air pollutant that is receiving intense regulatory attention in Taiwan. In previous studies, the effect of air pollution on bladder cancer has been explored. This study was conducted to elucidate the effect of atmospheric PM2.5 and other local risk factors on bladder cancer mortality based on available 13-year mortality data. Geographically weighted regress...

Recognition of the limitations of traditional hedonic models to account for spatial effects has led in recent years to the development and use of spatial econometric and statistical techniques in real estate applications. It seems appropriate, as the number of applications grows, to evaluate the relative ability of some newer approaches in terms of producing accurate spatial predictions. This a...

This study aims to develop a method for multivariate spatial overdispersion count data with mixed Poisson distribution, namely the Geographically Weighted Multivariate Inverse Gaussian Regression (GWMPIGR) model. The parameters of GWMPIGR model are estimated locally using maximum likelihood estimation (MLE) by considering effects. Therefore, significance regression parameter differs each locati...

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