Using Geographically Weighted Poisson Regression for county-level crash modeling in California

Safety Science

Volumn 58, Issue , 2013, Pages 89-97

  Li, Zhibin ^a,b   Wang, Wei ^a   Liu, Pan ^a   Bigham, John M ^b   Ragland, David R ^b  

^a SOUTHEAST UNIVERSITY   (China)

^b Berkeley   (United States)

Author keywords

County level; Crash; Geographically Weighted Regression; Safety

Indexed keywords

COUNTY-LEVEL; CRASH; EXPLANATORY VARIABLES; GEOGRAPHICALLY WEIGHTED REGRESSION; SOCIO-DEMOGRAPHIC CHARACTERISTICS; SPATIAL CORRELATIONS; SPATIAL HETEROGENEITY; SPATIALLY NON STATIONARIES;

ACCIDENT PREVENTION; FORECASTING; POISSON DISTRIBUTION; TRAFFIC CONTROL;

MAXIMUM LIKELIHOOD;

ARTICLE; CONTROLLED STUDY; CORRELATION ANALYSIS; DATA ANALYSIS; GEOGRAPHICALLY WEIGHTED POISSON REGRESSION; INTERMETHOD COMPARISON; LINEAR SYSTEM; MATHEMATICAL MODEL; PREDICTION; PRIORITY JOURNAL; REGRESSION ANALYSIS; TRAFFIC ACCIDENT; UNITED STATES;

EID: 84877913445     PISSN: 09257535     EISSN: 18791042     Source Type: Journal    
DOI: 10.1016/j.ssci.2013.04.005     Document Type: Article

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