Modeling crash spatial heterogeneity: Random parameter versus geographically weighting

Accident Analysis and Prevention

Volumn 75, Issue , 2015, Pages 16-25

  Xu, Pengpeng ^a   Huang, Helai ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

Author keywords

Random parameter negative binomial model; Regional crash prediction model; Semi parametric geographically weighted Poisson regression model; Spatial heterogeneity

Indexed keywords

MATHEMATICAL MODELS; POISSON DISTRIBUTION; REGRESSION ANALYSIS;

AKAIKE INFORMATION CRITERION; BAYESIAN NEGATIVE BINOMIAL; CONDITIONAL AUTOREGRESSIVE; CRASH PREDICTION; GEOGRAPHICALLY WEIGHTED POISSON REGRESSION MODELS; NEGATIVE BINOMIAL MODELS; SPATIAL HETEROGENEITY; UNOBSERVED HETEROGENEITY;

ACCIDENTS;

BAYES THEOREM; ENVIRONMENTAL PLANNING; HUMAN; PREVENTION AND CONTROL; SAFETY; SPATIAL REGRESSION; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TRAFFIC ACCIDENT; UNITED STATES;

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

EID: 84911901180     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2014.10.020     Document Type: Article

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