This paper examines the association between religious adherence and fertility rates across counties in the United States (1998-2002), controlling for other demographic and socioeconomic variables. Employing geographically weighted regression (GWR) analysis, this study finds that the relationship between religion and fertility differs remarkably over space, illustrating different spatial pattern...

Modeling the relationships between environment, human activity, and natural conditions is very important for understanding human-environment interactions. This study aims at examining how these relationships vary over spatial sampling scales and investigating the spatially varying relationships between land-cover changes and driving factors, as well as the variations in the relationships at dif...

Land resource management requires extensive land mapping. Conventional soil mapping takes a long time and is expensive; therefore, geographic information system data as predictor in texture modeling can be used an alternative solution to shorten reduce costs. Through digital elevation model data, topographic variability obtained independent variable predicting texture. Geographically weighted r...

A Bayesian treatment of locally linear regression methods introduced in McMillen (1996) and labeled geographically weighted regressions (GWR) in Brunsdon, Fotheringham and Charlton (1996) is set forth in this paper. GWR uses distance-decay-weighted sub-samples of the data to produce locally linear estimates for every point in space. While the use of locally linear regression represents a true c...