文章基本信息

标题：Dynamic Statistical Model Selection: Application to Traffic Accident Analysis in Spain
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作者：Bahar Dadashova ; Bahar Dadashova ; Blanca Arenas Ramírez 等
期刊名称：Procedia - Social and Behavioral Sciences
印刷版ISSN：1877-0428
出版年度：2012
卷号：48
页码：642-652
DOI：10.1016/j.sbspro.2012.06.1042
语种：English
出版社：Elsevier
摘要：AbstractFour time series: number and severity of both van accidents and victims in Spanish roads have been estimated using two main types of methodologies which are applied in the study of traffic accidents: demand for road use, accidents and their gravity (DRAG) and unobserved components model (UCM). Each model was estimated using explanatory and intervention variables that were divided into 9 groups. The explanatory variables were included in the models depending on how significant their t-values were. The final models were chosen using fit statistics such as AIC and R2. Finally, predictions were obtained by both methodologies and the prediction errors were compared. None of the two methods was clearly better; it depended on which response variable was being predicted.
关键词：DRAG;unobserved components model;traffic accidetns;prediction error