Bayesian model selection of structural explanatory models: Application to road accident data

Dadashova, Bahar and Arenas Ramírez, Blanca del Valle and Mira McWilliams, José Manuel and Aparicio Izquierdo, Francisco (2014). Bayesian model selection of structural explanatory models: Application to road accident data. "Procedia - Social and Behavioral Sciences", v. 160 (n. null); pp. 55-63. ISSN 1877-0428. https://doi.org/10.1016/j.sbspro.2014.12.116.

Description

Title: Bayesian model selection of structural explanatory models: Application to road accident data
Author/s:
  • Dadashova, Bahar
  • Arenas Ramírez, Blanca del Valle
  • Mira McWilliams, José Manuel
  • Aparicio Izquierdo, Francisco
Item Type: Article
Título de Revista/Publicación: Procedia - Social and Behavioral Sciences
Date: 2014
Volume: 160
Subjects:
Freetext Keywords: Structural explanatory models; Box-Cox transformation; Bayesian inference; Markov Chain Monte Carlo; Gibbs sampling, traffic accidents; crash prediction
Faculty: Instituto de Investigación del Automóvil (INSIA) (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Using the Bayesian approach as the model selection criteria, the main purpose in this study is to establish a practical road accident model that can provide a better interpretation and prediction performance. For this purpose we are using a structural explanatory model with autoregressive error term. The model estimation is carried out through Bayesian inference and the best model is selected based on the goodness of fit measures. To cross validate the model estimation further prediction analysis were done. As the road safety measures the number of fatal accidents in Spain, during 2000-2011 were employed. The results of the variable selection process show that the factors explaining fatal road accidents are mainly exposure, economic factors, and surveillance and legislative measures. The model selection shows that the impact of economic factors on fatal accidents during the period under study has been higher compared to surveillance and legislative measures.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTRA2011-28647-C02-0UnspecifiedUnspecifiedUnspecified

More information

Item ID: 33335
DC Identifier: http://oa.upm.es/33335/
OAI Identifier: oai:oa.upm.es:33335
DOI: 10.1016/j.sbspro.2014.12.116
Official URL: http://www.sciencedirect.com/science/article/pii/S187704281406217X
Deposited by: Memoria Investigacion
Deposited on: 06 Feb 2015 16:27
Last Modified: 06 May 2019 07:17
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