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Memorias de investigación
Research Publications in journals:
Bayesian Model Selection of Structural Explanatory Models: Application to Road Accident Data
Year:2014
Research Areas
  • Engineering
Information
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.
International
Si
JCR
No
Title
Procedia - Social and Behavioral Sciences
ISBN
1877-0428
Impact factor JCR
Impact info
Volume
160
doi:10.1016/j.sbspro.2014.12.116
Journal number
From page
55
To page
63
Month
SIN MES
Ranking
Participants
  • Autor: Bahar Dadashova . (UPM)
  • Autor: Blanca del Valle Arenas Ramirez (UPM)
  • Autor: Jose Manuel Mira Mcwilliams (UPM)
  • Autor: Francisco Aparicio Izquierdo (UPM)
Research Group, Departaments and Institutes related
  • Creador: Departamento: Ingeniería de Organización, Administración de Empresas y Estadística
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Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
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