Observatorio de I+D+i UPM

Memorias de investigación
Artículos en revistas:
Bayesian Model Selection of Structural Explanatory Models: Application to Road Accident Data
Año:2014
Áreas de investigación
  • Ingenierías
Datos
Descripción
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.
Internacional
Si
JCR del ISI
No
Título de la revista
Procedia - Social and Behavioral Sciences
ISSN
1877-0428
Factor de impacto JCR
Información de impacto
Volumen
160
DOI
doi:10.1016/j.sbspro.2014.12.116
Número de revista
Desde la página
55
Hasta la página
63
Mes
SIN MES
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Participantes
  • Autor: Bahar Dadashova . (UPM)
  • Autor: Blanca del Valle Arenas Ramirez (UPM)
  • Autor: Jose Manuel Mira Mcwilliams (UPM)
  • Autor: Francisco Aparicio Izquierdo (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Ingeniería de Organización, Administración de Empresas y Estadística
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