Anastasopoulos Panagiotis Ch, Mannering Fred L
School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907-2051, USA.
Accid Anal Prev. 2009 Jan;41(1):153-9. doi: 10.1016/j.aap.2008.10.005. Epub 2008 Nov 7.
In recent years there have been numerous studies that have sought to understand the factors that determine the frequency of accidents on roadway segments over some period of time, using count data models and their variants (negative binomial and zero-inflated models). This study seeks to explore the use of random-parameters count models as another methodological alternative in analyzing accident frequencies. The empirical results show that random-parameters count models have the potential to provide a fuller understanding of the factors determining accident frequencies.
近年来,有大量研究试图通过计数数据模型及其变体(负二项式模型和零膨胀模型)来理解在一段时间内决定道路路段事故发生频率的因素。本研究旨在探索使用随机参数计数模型作为分析事故频率的另一种方法选择。实证结果表明,随机参数计数模型有可能更全面地理解决定事故频率的因素。