Bayesian spatiotemporal crash frequency models with mixture components for space-time interactions

Accident Analysis and Prevention

Volumn 112, Issue , 2018, Pages 84-93

  Cheng, Wen ^a   Gill, Gurdiljot Singh ^a   Zhang, Yongping ^a   Cao, Zhong ^b  

^a CALIFORNIA STATE POLYTECHNIC UNIVERSITY   (United States)

^b GUANGZHOU UNIVERSITY   (China)

Author keywords

Cross validation; Interaction; Mixture; Predictive accuracy; Spatiotemporal; Time adjacency

Indexed keywords

FORECASTING; RANDOM PROCESSES; SAFETY ENGINEERING; TEMPORAL LOGIC; TRAFFIC CONTROL;

CROSS VALIDATION; INTERACTION; PREDICTIVE ACCURACY; SPATIOTEMPORAL; TIME ADJACENCY;

MIXTURES;

BAYES THEOREM; ENVIRONMENTAL PLANNING; EVALUATION STUDY; HUMAN; PREVENTION AND CONTROL; SAFETY; SPATIAL ANALYSIS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TRAFFIC ACCIDENT;

ACCIDENTS, TRAFFIC; BAYES THEOREM; ENVIRONMENT DESIGN; HUMANS; MODELS, STATISTICAL; SAFETY; SPATIAL ANALYSIS;

EID: 85040333450     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2017.12.020     Document Type: Article

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