Articles | Volume 13, issue 12
https://doi.org/10.5194/gmd-13-6149-2020
https://doi.org/10.5194/gmd-13-6149-2020
Model description paper
 | 
03 Dec 2020
Model description paper |  | 03 Dec 2020

A spatiotemporal weighted regression model (STWR v1.0) for analyzing local nonstationarity in space and time

Xiang Que, Xiaogang Ma, Chao Ma, and Qiyu Chen

Viewed

Total article views: 5,165 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,525 1,570 70 5,165 78 66
  • HTML: 3,525
  • PDF: 1,570
  • XML: 70
  • Total: 5,165
  • BibTeX: 78
  • EndNote: 66
Views and downloads (calculated since 18 Mar 2020)
Cumulative views and downloads (calculated since 18 Mar 2020)

Viewed (geographical distribution)

Total article views: 5,165 (including HTML, PDF, and XML) Thereof 4,537 with geography defined and 628 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Apr 2024
Download
Short summary
This paper presents a spatiotemporal weighted regression (STWR) model for exploring nonstationary spatiotemporal processes in nature and socioeconomics. A value change rate is introduced in the temporal kernel, which presents significant model fitting and accuracy in both simulated and real-world data. STWR fully incorporates observed data in the past and outperforms geographic temporal weighted regression (GTWR) and geographic weighted regression (GWR) models in several experiments.