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Modeling road traffic crashes with zero-inflation and site-specific random effects

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  • Helai Huang
  • Hong Chin

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  • Helai Huang & Hong Chin, 2010. "Modeling road traffic crashes with zero-inflation and site-specific random effects," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(3), pages 445-462, August.
    • Handle: RePEc:spr:stmapp:v:19:y:2010:i:3:p:445-462
    DOI: 10.1007/s10260-010-0136-x
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    References listed on IDEAS

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    1. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    2. Angers, Jean-Francois & Biswas, Atanu, 2003. "A Bayesian analysis of zero-inflated generalized Poisson model," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 37-46, February.
    3. Yip, Karen C.H. & Yau, Kelvin K.W., 2005. "On modeling claim frequency data in general insurance with extra zeros," Insurance: Mathematics and Economics, Elsevier, vol. 36(2), pages 153-163, April.
    4. A. M. C. Vieira & J. P. Hinde & C. G. B. Demetrio, 2000. "Zero-inflated proportion data models applied to a biological control assay," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(3), pages 373-389.
    5. KENNETH C. LAND & PATRICIA L. McCALL & DANIEL S. NAGIN, 1996. "A Comparison of Poisson, Negative Binomial, and Semiparametric Mixed Poisson Regression Models," Sociological Methods & Research, , vol. 24(4), pages 387-442, May.
    6. Xie, M. & He, B. & Goh, T. N., 2001. "Zero-inflated Poisson model in statistical process control," Computational Statistics & Data Analysis, Elsevier, vol. 38(2), pages 191-201, December.
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    Cited by:

    1. Feng Chen & Suren Chen & Xiaoxiang Ma, 2016. "Crash Frequency Modeling Using Real-Time Environmental and Traffic Data and Unbalanced Panel Data Models," IJERPH, MDPI, vol. 13(6), pages 1-16, June.
    2. Shenjun Yao & Jinzi Wang & Lei Fang & Jianping Wu, 2018. "Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China," Sustainability, MDPI, vol. 10(12), pages 1-11, December.
    3. Ciro Caliendo & Maurizio Guida & Fabio Postiglione & Isidoro Russo, 2022. "A Bayesian bivariate hierarchical model with correlated parameters for the analysis of road crashes in Italian tunnels," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 109-131, March.
    4. María Flor & Armando Ortuño & Begoña Guirao, 2022. "Does the Implementation of Ride-Hailing Services Affect Urban Road Safety? The Experience of Madrid," IJERPH, MDPI, vol. 19(5), pages 1-18, March.
    5. Hu, Junjie & Hu, Cheng & Yang, Jiayu & Bai, Jun & Lee, Jaeyoung Jay, 2024. "Do traffic flow states follow Markov properties? A high-order spatiotemporal traffic state reconstruction approach for traffic prediction and imputation," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).

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