Federal University Reports Findings in Risk Management (Geographically weighted negative binomial regression applied to zonal level safety…
Federal University Reports Findings in Risk Management (Geographically weighted negative binomial regression applied to zonal level safety performance models)
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According to the news editors, the research concluded: "The models were calibrated by using the frequency of injury crashes as a dependent variable and the results showed that GWPR and GWNBR achieved a better performance than GLM for the average residuals and likelihood as well as reducing the spatial autocorrelation of the residuals, and the GWNBR model was more able to capture the spatial heterogeneity of the crash frequency."
For more information on this research see: Geographically weighted negative binomial regression applied to zonal level safety performance models. Accident Analysis and Prevention, 2017;106():254-261. Accident Analysis and Prevention can be contacted at:
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The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.aap.2017.06.011. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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