NetPointLib: Library for Large-Scale Spatial Network Point Data Fusion and Analysis
Author:
Affiliation:
1. Department of Geography and Geographic Information Science, University of Illinois Urbana-Champaign, USA
2. Virginia Tech, USA
3. University of Illinois Urbana-Champaign, USA
Funder
National Science Foundation
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3626203.3670615
Reference14 articles.
1. Inhomogeneous higher-order summary statistics for point processes on linear networks
2. Inhomogeneous spatio-temporal point processes on linear networks for visitors’ stops data
3. Nicoletta D’Angelo, David Payares, Giada Adelfio, and Jorge Mateu. 2022. Self-exciting point process modelling of crimes on linear networks. Statistical Modelling (2022), 1471082X221094146.
4. Matthias Eckardt and Mehdi Moradi. 2023. Marked spatial point processes: current state and extensions to point processes on linear networks. https://doi.org/10.48550/arXiv.2309.01511 arXiv:2309.01511 [stat].
5. Chance Haycock, Edward Thorpe-Woods, James Walsh, Patrick O’Hara, Oscar Giles, Neil Dhir, and Theodoros Damoulas. 2020. An expectation-based network scan statistic for a covid-19 early warning system. arXiv preprint arXiv:2012.07574 (2020).
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