Journal Article10.1016/J.AAP.2015.11.006
A multivariate spatial crash frequency model for identifying sites with promise based on crash types
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TL;DR: This study responds to the need for more precise statistical output and proposes a multivariate spatial model for simultaneously modeling crash frequencies for different crash types and found that the multivariate correlation plays a stronger role than the spatial correlation when modelingCrash frequencies in terms of different crash type.
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About: This article is published in Accident Analysis & Prevention. The article was published on 01 Feb 2016. The article focuses on the topics: Crash & Multivariate statistics.
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Citations
A review of spatial approaches in road safety
TL;DR: The use of different areal unit levels in spatial road safety studies is investigated, different modelling approaches are discussed, and the corresponding study design characteristics are summarized in respective tables including traffic, road environment and area parameters and spatial aggregation approaches.
186
A multivariate spatial model of crash frequency by transportation modes for urban intersections
TL;DR: In this article, a multivariate spatial model was proposed to simultaneously analyze the occurrence of motor vehicle, bicycle and pedestrian crashes at urban intersections, which can account for both the correlation among different modes involved in crashes at individual intersections and spatial correlation between adjacent intersections.
133
Multivariate space-time modeling of crash frequencies by injury severity levels
TL;DR: In this paper, a multivariate space-time model is proposed for predicting crash frequencies of different injury severity levels, including spatial correlation and/or heterogeneity, temporal correlation and or heterogeneity, and correlations between crash frequencies.
115
Using the multivariate spatio-temporal Bayesian model to analyze traffic crashes by severity
Chenhui Liu,Anuj Sharma +1 more
TL;DR: In this article, the authors analyzed the yearly county-level fatal, major injury, and minor injury crashes in Iowa from 2006 to 2015 using a multivariate spatio-temporal Bayesian model.
97
Developing a grouped random parameters multivariate spatial model to explore zonal effects for segment and intersection crash modeling
TL;DR: In this article, a grouped random parameters multivariate spatial model is proposed to identify both observable zonal effects and unobserved heterogeneity at the zonal level by considering the heterogeneous and spatial correlations.
89
References
Bayesian measures of model complexity and fit
TL;DR: In this paper, the authors consider the problem of comparing complex hierarchical models in which the number of parameters is not clearly defined and derive a measure pD for the effective number in a model as the difference between the posterior mean of the deviances and the deviance at the posterior means of the parameters of interest, which is related to other information criteria and has an approximate decision theoretic justification.
•Journal Article
Bayesian measures of model complexity and fit
TL;DR: The posterior mean deviance is suggested as a Bayesian measure of fit or adequacy, and the contributions of individual observations to the fit and complexity can give rise to a diagnostic plot of deviance residuals against leverages.
7.6K
•Book
Bayes and Empirical Bayes Methods for Data Analysis
Bradley P. Carlin,Thomas A. Louis +1 more
- 15 May 1996
TL;DR: Approaches for Statistical Inference: The Bayes Approach, Model Criticism and Selection, and Performance of Bayes Procedures.