A method to account for outliers in the development of safety performance functions

Accident Analysis and Prevention

Volumn 42, Issue 4, 2010, Pages 1266-1272

  El Basyouny, Karim ^a   Sayed, Tarek ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Contaminated normal models; Discrete mixtures; Full Bayes estimation; Markov Chain Monte Carlo; Multivariate Poisson lognormal regression; Outlier detection; Scale mixture models; Student t models

Indexed keywords

BAYES ESTIMATION; DISCRETE MIXTURE; LOG-NORMAL; MARKOV CHAIN MONTE CARLO; MIXTURE MODEL; NORMAL MODEL; OUTLIER DETECTION; SCALE-MIXTURE MODELS; T-MODEL;

MARKOV PROCESSES; MONTE CARLO METHODS; NORMAL DISTRIBUTION; POISSON DISTRIBUTION; REGRESSION ANALYSIS; STATISTICS; STUDENTS; UNCERTAINTY ANALYSIS;

MIXTURES;

ARTICLE; HUMAN; MULTIVARIATE ANALYSIS; NORMAL DISTRIBUTION; POISSON DISTRIBUTION; REGRESSION ANALYSIS; REPRODUCIBILITY; SAFETY; STATISTICAL MODEL; STATISTICS; TRAFFIC ACCIDENT;

ACCIDENTS, TRAFFIC; HUMANS; MODELS, STATISTICAL; MULTIVARIATE ANALYSIS; NORMAL DISTRIBUTION; POISSON DISTRIBUTION; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SAFETY;

EID: 77955338512     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2010.02.003     Document Type: Article

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