A note on modeling vehicle accident frequencies with random-parameters count models.
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.
Anastasopoulos
Panagiotis Ch
PCh
School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907-2051, USA. panast@purdue.edu
Mannering
Fred L
FL
D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001334:Automobile Driving / Q000706:statistics & numerical data; D006801:Humans; D015233:Models, Statistical; D016012:Poisson Distribution; D014481:United States / Q000453:epidemiology