Big data has now become a strong focus of global interest that is increasingly attracting the
attention of academia, industry, government and other organizations. Big data can be …

ABSTRACT Geographically Weighted Regression (GWR) has been broadly used in various
fields to model spatially non-stationary relationships. Multi-scale Geographically Weighted …

空间数据关系中的异质性或非**稳性特征是**期空间统计或相关应用领域的研究热点之一,
而局部空间统计分析技术的提出与发展是其关键环节. 地理加权回归分析技术(geographically …

ABSTRACT Geographically Weighted Regression (GWR) is a widely used tool for exploring
spatial heterogeneity of processes over geographic space. GWR computes location-specific …

BACKGROUND Demography is an inherently spatial science, yet the application of spatial
data and methods to demographic research has tended to lag that of other disciplines. In …

As an established spatial analytical tool, Geographically Weighted Regression (GWR) has
been applied across a variety of disciplines. However, its usage can be challenging for large …

As more and more real time spatio-temporal datasets become available at increasing spatial
and temporal resolutions, the provision of high quality, predictive information about spatio …

Incident data, a form of big data frequently used in urban studies, are characterized by point
features with high spatial and temporal resolution and categorical values. In contrast to …

This study develops a spatially varying coefficient model by extending the random effects
eigenvector spatial filtering model. The developed model has the following properties: its …

Although a number of studies have developed fast geographically weighted regression
(GWR) algorithms for large samples, none of them has achieved linear-time estimation …