Lecture

Geographically Weighted Regression

Description

This lecture covers Geographically Weighted Regression (GWR), a method for exploring spatial non-stationarity in relationships between variables. It discusses the basic hypothesis, influence of explanatory variables, W Matrix, Kernel functions, and the comparison between Ordinary Least Squares (OLS) and GWR. The lecture also includes a case study on estimating net primary production in Chinese forest ecosystems using GWR. Conclusions highlight the advantages of GWR in providing location-specific insights and reducing bias compared to OLS.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_tt4bz4t8

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis

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