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elwood-spatial: Information-Theoretic Outlier Detection for Spatial Networks

Authors: Stuart Illson;

elwood-spatial: Information-Theoretic Outlier Detection for Spatial Networks

Abstract

Much of this code has been ported over from operational scripts currently doing outlier detection for production feeds. Everything was specific and procedural, and I have made efforts to abstract out the core logic, and make this less tied to surface observations of air quality, and make it broadly applicable to any graph/network structure — although it's primarily designed for spatial, environmental monitoring networks. I provided a pattern and logic and co-authored this with Claude. As this is in beta, there is a lot that can change, particularly with the scope and functionality of this package. This draft release will be used to generate a DOI for a paper that references this method, hopefully to be published within the year. Please contact with questions.

If you use this software, please cite it as below.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average