Our new research paper “SGWR: similarity and geographically weighted regression” is published in the International Journal of Geographical Information Science (IJGIS). In this study, we extend the geographically weighted regression (GWR) by integrating attribute similarity alongside the conventional geographically weighted matrix. The new model, called SGWR, was evaluated across various datasets, including housing prices, crime rates, and three health outcomes including mental health, depression, and HIV. Results show that SGWR consistently outperforms the global regression model and the traditional GWR based on several statistical measures across all experimental datasets.
Read the full article (open access) at https://lnkd.in/enejjskZ
Code and datasets are available at https://lnkd.in/e4Yn6xyP
Graphic user interface (GUI) for SGWR is under development. Stay tuned!
