Graph Regression Model for Spatial and Temporal Environmental Data—Case of Carbon Dioxide Emissions in the United States
We develop a new model for spatio-temporal data. More specifically, a graph penalty function is incorporated in the cost function in order to estimate the unknown parameters of a spatio-temporal mixed-effect model based on a generalized linear model. This model allows for more flexible and general r...
Main Authors: | Roméo Tayewo, François Septier, Ido Nevat, Gareth W. Peters |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-08-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/25/9/1272 |
Similar Items
-
Leveraging Spatio-Temporal Graphs and Knowledge Graphs: Perspectives in the Field of Maritime Transportation
by: Géraldine Del Mondo, et al.
Published: (2021-08-01) -
The Spatio-Temporal Distribution Characteristics of Carbon Dioxide Derived from the Trajectory Mapping of Ground Observation Network Data in Shanxi Province, One of China’s Largest Emission Regions
by: Fengsheng Zhang, et al.
Published: (2024-01-01) -
Day-Ahead Hourly Solar Irradiance Forecasting Based on Multi-Attributed Spatio-Temporal Graph Convolutional Network
by: Hyeon-Ju Jeon, et al.
Published: (2022-09-01) -
Analyzing Shared Bike Usage Through Graph-Based Spatio-Temporal Modeling
by: Dinh Viet Cuong, et al.
Published: (2024-01-01) -
Spatio-Temporal Dual Kriging with Adaptive Coefficient Drift Function
by: Chalida Kongsanun, et al.
Published: (2024-01-01)