Modelling low temporal, large spatial data of fatal crashes: An application of negative binomial GSARIMAX time series.

Ghalehnovi S, Mohammadzadeh Moghaddam A, Mohammadpour SI

DOI: 10.1016/j.aap.2025.107958
Published: 2025 May
Container: Accident; analysis and prevention
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1016/j.aap.2025.107958,
  title = {Modelling low temporal, large spatial data of fatal crashes: An application of negative binomial GSARIMAX time series.},
  author = {Ghalehnovi S and Mohammadzadeh Moghaddam A and Mohammadpour SI},
  year = {2025},
  journal = {Accident; analysis and prevention},
  doi = {10.1016/j.aap.2025.107958},
  url = {https://doi.org/10.1016/j.aap.2025.107958}
}

RIS

TY  - JOUR
TI  - Modelling low temporal, large spatial data of fatal crashes: An application of negative binomial GSARIMAX time series.
AU  - Ghalehnovi S
AU  - Mohammadzadeh Moghaddam A
AU  - Mohammadpour SI
PY  - 2025
JO  - Accident; analysis and prevention
DO  - 10.1016/j.aap.2025.107958
UR  - https://doi.org/10.1016/j.aap.2025.107958
ER  -

APA

S, G., A, M. M., & SI, M. (2025). Modelling low temporal, large spatial data of fatal crashes: An application of negative binomial GSARIMAX time series.. Accident; analysis and prevention. https://doi.org/10.1016/j.aap.2025.107958

Source records

pubmed · retrieved 2026-09-26T07:53:06.920Z