Bayesian model selection methodology for road safety

Dadashova, Bahar; Arenas Ramírez, Blanca del Valle; Mira McWilliams, José Manuel y Aparicio Izquierdo, Francisco (2014). Bayesian model selection methodology for road safety. En: "8th International Conference on Computational and Financial Econometrics and 7th International Conference of the ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on Computational and Methodological Statistics", 06/12/2014 - 08/12/2014, Pisa, Italy. ISBN 978-84-937822-4-5. p. 65.

Descripción

Título: Bayesian model selection methodology for road safety
Autor/es:
  • Dadashova, Bahar
  • Arenas Ramírez, Blanca del Valle
  • Mira McWilliams, José Manuel
  • Aparicio Izquierdo, Francisco
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 8th International Conference on Computational and Financial Econometrics and 7th International Conference of the ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on Computational and Methodological Statistics
Fechas del Evento: 06/12/2014 - 08/12/2014
Lugar del Evento: Pisa, Italy
Título del Libro: CFE-ERCIM 2014. PROGRAMME AND ABSTRACTS
Fecha: 2014
ISBN: 978-84-937822-4-5
Materias:
Escuela: Instituto de Investigación del Automóvil (INSIA) (UPM)
Departamento: Otro
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Road accidents are a very relevant issue in many countries and macroeconomic models are very frequently applied by academia and administrations to reduce their frequency and consequences. The selection of explanatory variables and response transformation parameter within the Bayesian framework for the selection of the set of explanatory variables a TIM and 3IM (two input and three input models) procedures are proposed. The procedure also uses the DIC and pseudo -R2 goodness of fit criteria. The model to which the methodology is applied is a dynamic regression model with Box-Cox transformation (BCT) for the explanatory variables and autorgressive (AR) structure for the response. The initial set of 22 explanatory variables are identified. The effects of these factors on the fatal accident frequency in Spain, during 2000-2012, are estimated. The dependent variable is constructed considering the stochastic trend component.

Más información

ID de Registro: 33310
Identificador DC: http://oa.upm.es/33310/
Identificador OAI: oai:oa.upm.es:33310
URL Oficial: http://www.cfenetwork.org/CFE2014/
Depositado por: Memoria Investigacion
Depositado el: 09 Feb 2015 16:53
Ultima Modificación: 24 Feb 2017 16:36
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