A route map for successful applications of geographically weighted regression
Geographically Weighted Regression (GWR) is increasingly used in spatial analyses of
social and environmental data. It allows spatial heterogeneities in processes and …
social and environmental data. It allows spatial heterogeneities in processes and …
Targeting the spatial context of obesity determinants via multiscale geographically weighted regression
Background Obesity rates are recognized to be at epidemic levels throughout much of the
world, posing significant threats to both the health and financial security of many nations …
world, posing significant threats to both the health and financial security of many nations …
Replication across space and time must be weak in the social and environmental sciences
MF Goodchild, W Li - … of the National Academy of Sciences, 2021 - National Acad Sciences
Replicability takes on special meaning when researching phenomena that are embedded in
space and time, including phenomena distributed on the surface and near surface of the …
space and time, including phenomena distributed on the surface and near surface of the …
Inference in multiscale geographically weighted regression
A recent paper expands the well‐known geographically weighted regression (GWR)
framework significantly by allowing the bandwidth or smoothing factor in GWR to be derived …
framework significantly by allowing the bandwidth or smoothing factor in GWR to be derived …
Modeling the spatially heterogeneous relationships between tradeoffs and synergies among ecosystem services and potential drivers considering geographic scale in …
C Xue, X Chen, L Xue, H Zhang, J Chen, D Li - Science of the Total …, 2023 - Elsevier
Understanding the complex relationships of tradeoffs and synergies among ecosystem
services (ESs) is essential to achieve a comprehensive, coordinated, and sustainable …
services (ESs) is essential to achieve a comprehensive, coordinated, and sustainable …
Sociodemographic determinants of COVID-19 incidence rates in Oman: Geospatial modelling using multiscale geographically weighted regression (MGWR)
The current COVID-19 pandemic is evolving rapidly into one of the most devastating public
health crises in recent history. By mid-July 2020, reported cases exceeded 13 million …
health crises in recent history. By mid-July 2020, reported cases exceeded 13 million …
Spatial econometrics
L Anselin - Handbook of spatial analysis in the social sciences, 2022 - elgaronline.com
In many instances in empirical spatial analysis, the method of choice is a regression
analysis, whereby a variable of interest (the dependent variable) is related in a linear way to …
analysis, whereby a variable of interest (the dependent variable) is related in a linear way to …
[HTML][HTML] A retrospective cross-national examination of COVID-19 outbreak in 175 countries: a multiscale geographically weighted regression analysis (January 11 …
Objective This study retrospectively examined the health and social determinants of the
COVID-19 outbreak in 175 countries from a spatial epidemiological approach. Methods We …
COVID-19 outbreak in 175 countries from a spatial epidemiological approach. Methods We …
Computational improvements to multi-scale geographically weighted regression
ABSTRACT Geographically Weighted Regression (GWR) has been broadly used in various
fields to model spatially non-stationary relationships. Multi-scale Geographically Weighted …
fields to model spatially non-stationary relationships. Multi-scale Geographically Weighted …
Reproducibility and replicability in geographical analysis
The scientific method is predicated on the assumption that research designs and results can
be reproduced and replicated. However, recent findings in some disciplines suggest that …
be reproduced and replicated. However, recent findings in some disciplines suggest that …