Geographically Weighted Regression

Geographically Weighted Regression (GWR) is an analytical method that examines how relationships between factors vary across different locations. Instead of using a single equation for an entire area, GWR creates local models for specific places, taking into account nearby data. For example, it can show how the relationship between income and education level differs between neighborhoods. This approach helps reveal spatial patterns and local variations, providing a nuanced understanding of how factors influence outcomes differently across regions. It’s useful for making more precise, location-specific insights in fields like urban planning, environmental science, and public health.