  Local spatial models such as Geographically Weighted Regression (GWR) and
Multiscale Geographically Weighted Regression (MGWR) serve as instrumental
tools to capture intrinsic contextual effects through the estimates of the
local intercepts and behavioral contextual effects through estimates of the
local slope parameters. GWR and MGWR provide simple implementation yet powerful
frameworks that could be extended to various disciplines that handle spatial
data. This bibliography aims to serve as a comprehensive compilation of
peer-reviewed papers that have utilized GWR or MGWR as a primary analytical
method to conduct spatial analyses and acts as a useful guide to anyone
searching the literature for previous examples of local statistical modeling in
a wide variety of application fields.
