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Transportmetrica A: Transport Science Volume 14, 2018 - Issue 3
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Original Articles

A joint econometric framework for modeling crash counts by severity

Shamsunnahar YasminDepartment of Civil, Environmental & Construction Engineering, University of Central Florida, Orlando, FL, USA
&
Naveen EluruDepartment of Civil, Environmental & Construction Engineering, University of Central Florida, Orlando, FL, USACorrespondence[email protected]
ORCID Iconhttp://orcid.org/0000-0003-1221-4113
ORCID Icon
Pages 230-255 | Received 13 Nov 2016, Accepted 15 Aug 2017, Published online: 03 Sep 2017

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Qiang Zeng, Fangzhou Wang, Qianfang Wang, Xin Pei & Quan Yuan. (2023) Bayesian multivariate spatial modeling for crash frequencies by injury severity at daytime and nighttime in traffic analysis zones. Transportation Letters 15:6, pages 553-560.
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Theodore Charm, Haoqi Wang, Natalia Zuniga-Garcia, Mostaq Ahmed & Kara M. Kockelman. (2023) Predicting crash occurrence at intersections in Texas: an opportunity for machine learning. Transportation Planning and Technology 0:0, pages 1-21.
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Pei-Fen Kuo, Dominique Lord, Umroh Dian Sulistyah & Ankit Jhamb. (2022) The impact of the great recession on the spatial patterns of traffic fatalities in Texas: a spatial point pattern test. Transportmetrica A: Transport Science 0:0, pages 1-19.
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Qiang Zeng, Qiang Guo, S. C. Wong, Huiying Wen, Heilai Huang & Xin Pei. (2019) Jointly modeling area-level crash rates by severity: a Bayesian multivariate random-parameters spatio-temporal Tobit regression. Transportmetrica A: Transport Science 15:2, pages 1867-1884.
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Emad Soroori, Abolfazl Mohammadzadeh Moghaddam & Mahdi Salehi. (2019) Application of local conditional autoregressive models for development of zonal crash prediction models and identification of crash risk boundaries. Transportmetrica A: Transport Science 15:2, pages 1102-1123.
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