Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
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 the fatal accidents (monthly data) involving vans were employed.
International
No
Congress
XI Congreso de Ingeniería del Transporte. CIT 2014
960
Place
Santander
Reviewers
Si
ISBN/ISSN
978-84-697-0359-5
Start Date
09/06/2014
End Date
11/06/2014
From page
1
To page
12
Actas del XI Congreso de Ingeniería del Transporte. CIT 2014
Participants
  • Autor: Bahar Dadashova . (UPM)
  • Autor: Jose Manuel Mira Mcwilliams (UPM)
  • Autor: Francisco Aparicio Izquierdo (UPM)
  • Autor: Blanca del Valle Arenas Ramirez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Estadística computacional y Modelado estocástico
  • Grupo de Investigación: Grupo de Inv. en Seguridad e Impacto Medioambiental de Vehículos y Transportes (GIVET)
  • Departamento: Ingeniería de Organización, Administración de Empresas y Estadística
  • Centro o Instituto I+D+i: Instituto Universitario de Investigación del Automóvil (INSIA)
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