Encapsulating Spatially Varying Relationships with a Generalized Additive Model

Encapsulating Spatially Varying Relationships with a Generalized Additive Model

This paper describes the use of Generalized Additive Models (GAMs) to create regression models whose coefficient estimates vary with geographic location—spatially varying coefficient (SVC) models. The approach uses Gaussian Process (GP) splines (smooths) for each predictor variable, which are parame...

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Bibliographic Details
Main Authors: Alexis Comber, Paul Harris, Daisuke Murakami, Tomoki Nakaya, Narumasa Tsutsumida, Takahiro Yoshida, Chris Brunsdon
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:ISPRS International Journal of Geo-Information
Subjects:
spatial analysis
process spatial heterogeneity
spatial regression
GAM
Online Access:https://www.mdpi.com/2220-9964/13/12/459

Internet

https://www.mdpi.com/2220-9964/13/12/459

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