Evaluating alternative variations of Negative Binomial–Lindley distribution for modelling crash data

Author:

Khodadadi Ali1ORCID,Shirazi Mohammadali2,Geedipally Srinivas3,Lord Dominique1

Affiliation:

1. Texas A&M University, College Station, TX, USA

2. University of Maine, Orono, ME, USA

3. Texas A&M Transportation Institute, Arlington, TX, USA

Funder

A.P. and Florence Wiley Faculty Fellow

Publisher

Informa UK Limited

Subject

General Engineering,Transportation

Reference52 articles.

1. Asgharpour, S., M. Javadinasr, and Z. Bayati. 2021. “Investigating Severity of Motorcycle-Involved Crashes in a Developing Country.” Presented at the 101th annual meeting of the Transportation Research Board (TRB), Washington, DC.

2. A new weighted Lindley distribution with application

3. Avelar, R., S. Geedipally, S. Das, L. Wu, B. Kutela, D. Lord, and I. Tsapakis. 2020. “Evaluation of Roadside Treatments to Mitigate Roadway Departure Crashes.” Tech. Rep. Texas A&M Transportation Institute.

4. Bakhshi, A. K., and M. M. Ahmed. 2021a. “Accounting for Human-Related Unobserved Heterogeneity in the Safety Performance of Connected Vehicles: an Incorporation of Bayesian Hierarchical Negative Binomial into Simulated Work Zone Warning Application.” IATSS Research.

5. Practical advantage of crossed random intercepts under Bayesian hierarchical modeling to tackle unobserved heterogeneity in clustering critical versus non-critical crashes

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