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

Dadashova, Bahar; Arenas Ramírez, Blanca del Valle; Mira McWilliams, José Manuel y 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.

Descripción

Título: Bayesian model selection of structural explanatory models: Application to road accident data
Autor/es:
  • Dadashova, Bahar
  • Arenas Ramírez, Blanca del Valle
  • Mira McWilliams, José Manuel
  • Aparicio Izquierdo, Francisco
Tipo de Documento: Artículo
Título de Revista/Publicación: Procedia - Social and Behavioral Sciences
Fecha: 2014
Volumen: 160
Materias:
Palabras Clave Informales: Structural explanatory models; Box-Cox transformation; Bayesian inference; Markov Chain Monte Carlo; Gibbs sampling, traffic accidents; crash prediction
Escuela: Instituto de Investigación del Automóvil (INSIA) (UPM)
Departamento: Otro
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 33335
Identificador DC: http://oa.upm.es/33335/
Identificador OAI: oai:oa.upm.es:33335
Identificador DOI: 10.1016/j.sbspro.2014.12.116
URL Oficial: http://www.sciencedirect.com/science/article/pii/S187704281406217X
Depositado por: Memoria Investigacion
Depositado el: 06 Feb 2015 16:27
Ultima Modificación: 24 Feb 2017 16:33
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