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A space–time multivariate Bayesian model to analyse road traffic accidents by severity

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  • Areti Boulieri
  • Silvia Liverani
  • Kees Hoogh
  • Marta Blangiardo

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  • Areti Boulieri & Silvia Liverani & Kees Hoogh & Marta Blangiardo, 2017. "A space–time multivariate Bayesian model to analyse road traffic accidents by severity," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 119-139, January.
    • Handle: RePEc:bla:jorssa:v:180:y:2017:i:1:p:119-139
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    File URL: http://hdl.handle.net/10.1111/rssa.12178
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    References listed on IDEAS

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    1. Ying C. MacNab & C. B. Dean, 2001. "Autoregressive Spatial Smoothing and Temporal Spline Smoothing for Mapping Rates," Biometrics, The International Biometric Society, vol. 57(3), pages 949-956, September.
    2. Tom Brijs & Dimitris Karlis & Filip Van den Bossche & Geert Wets, 2007. "A Bayesian model for ranking hazardous road sites," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 1001-1017, October.
    3. Mardia, K. V., 1988. "Multi-dimensional multivariate Gaussian Markov random fields with application to image processing," Journal of Multivariate Analysis, Elsevier, vol. 24(2), pages 265-284, February.
    4. Daniel J. Graham & Stephen Glaister, 2003. "Spatial Variation in Road Pedestrian Casualties: The Role of Urban Scale, Density and Land-use Mix," Urban Studies, Urban Studies Journal Limited, vol. 40(8), pages 1591-1607, July.
    5. Ludwig Fahrmeir & Stefan Lang, 2001. "Bayesian inference for generalized additive mixed models based on Markov random field priors," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(2), pages 201-220.
    6. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    7. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
    8. Frits Bijleveld & Jacques Commandeur & Siem Jan Koopman & Kees van Montfort, 2010. "Multivariate non‐linear time series modelling of exposure and risk in road safety research," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(1), pages 145-161, January.
    9. Song, J.J. & Ghosh, M. & Miaou, S. & Mallick, B., 2006. "Bayesian multivariate spatial models for roadway traffic crash mapping," Journal of Multivariate Analysis, Elsevier, vol. 97(1), pages 246-273, January.
    10. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
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    Cited by:

    1. Andrea Gilardi & Jorge Mateu & Riccardo Borgoni & Robin Lovelace, 2022. "Multivariate hierarchical analysis of car crashes data considering a spatial network lattice," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1150-1177, July.
    2. Bhowmik, Tanmoy & Yasmin, Shamsunnahar & Eluru, Naveen, 2021. "A New Econometric Approach for Modeling Several Count Variables: A Case Study of Crash Frequency Analysis by Crash Type and Severity," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 172-203.
    3. Briz-Redón, Álvaro & Iftimi, Adina & Montes, Francisco, 2022. "Accounting for previous events to model and predict traffic accidents at the road segment level: A study in Valencia (Spain)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    4. Beecham, Roger & Lovelace, Robin, 2022. "A framework for inserting visually-supported inferences into geographical analysis workflow: application to road safety research," OSF Preprints mfja8, Center for Open Science.

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