New Risk Management Data Have Been Reported by Investigators at South China University of Technology (A Bayesian spatial random parameters Tobit…

New Risk Management Data Have Been Reported by Investigators at South China University of Technology (A Bayesian spatial random parameters Tobit model for analyzing crash rates on roadway segments)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Investigators publish new report on Risk Management. According to news reporting originating in Guangdong, People's Republic of China, by VerticalNews journalists, research stated, "This study develops a Bayesian spatial random parameters Tobit model to analyze crash rates on road segments, in which both spatial correlation between adjacent sites and unobserved heterogeneity across observations are accounted for. The crash-rate data for a three-year period on road segments within a road network in Florida, are collected to compare the performance of the proposed model with that of a (fixed parameters) Tobit model and a spatial (fixed parameters) Tobit model in the Bayesian context."

Funders for this research include Natural Science Foundation of China, Joint Research Scheme of National Natural Science Foundation of China/Research Grants Council of Hong Kong.

The news reporters obtained a quote from the research from the South China University of Technology, "Significant spatial effect is found in both spatial models and the results of Deviance Information Criteria (DIC) show that the inclusion of spatial correlation in the Tobit regression considerably improves model fit, which indicates the reasonableness of considering cross-segment spatial correlation. The spatial random parameters Tobit regression has lower DIC value than does the spatial Tobit regression, suggesting that accommodating the unobserved heterogeneity is able to further improve model fit when the spatial correlation has been considered."

According to the news reporters, the research concluded: "Moreover, the random parameters Tobit model provides a more comprehensive understanding of the effect of speed limit on crash rates than does its fixed parameters counterpart, which suggests that it could be considered as a good alternative for crash rate analysis."

For more information on this research see: A Bayesian spatial random parameters Tobit model for analyzing crash rates on roadway segments. Accident Analysis and Prevention, 2017;100():37-43. Accident Analysis and Prevention can be contacted at: Pergamon-Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England. (Elsevier - www.elsevier.com; Accident Analysis and Prevention - www.journals.elsevier.com/accident-analysis-and-prevention/)

Our news correspondents report that additional information may be obtained by contacting Q. Zeng, South China Univ Technol, Sch Civil Engn & Transportat, Guangzhou 510641, Guangdong, People's Republic of China. Additional authors for this research include H.Y. Wen, H.L. Huang and M. Abdel-Aty.

Keywords for this news article include: Guangdong, People's Republic of China, Asia, Risk Management, South China University of Technology.

Our reports deliver fact-based news of research and discoveries from around the world. Copyright 2017, NewsRx LLC