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Conference object . 2024
License: CC BY
Data sources: ZENODO
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Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
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Analysing Shooting Incidents in New York Using Spatial Regression Techniques

Authors: Brunsdon, Chris;

Analysing Shooting Incidents in New York Using Spatial Regression Techniques

Abstract

Spatial regression techniques usually applied to area data are here adapted to work with network data - in this case road sections. An example is given exloring spatial patterns in shooting incidents in a neighbourhood of New York City, making use of open data. Risks of a shooting occuring are modeled using both Poisson and negative binomial distributions, and compared using an Aikake Information Criterion (AIC) approach - which suggests that the negative binomial model (in which events tend to cluster) is more plausible than the Poisson.

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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
Green