Bias properties of Bayesian statistics in finite mixture of negative binomial regression models in crash data analysis

Accident Analysis and Prevention

Volumn 42, Issue 2, 2010, Pages 741-749

  Park, Byung Jung ^a   Lord, Dominique ^a   Hart, Jeffrey D ^b  

^a Texas A and M University   (United States)

^b TEXAS A AND M UNIVERSITY   (United States)

Author keywords

Bayesian summary statistics; Bias; Finite mixture model; Heterogeneity; Negative binomial

Indexed keywords

BAYESIAN; BAYESIAN STATISTICS; BIAS PROPERTIES; CRASH DATA; DATA SETS; DISPERSION PARAMETERS; EMPIRICAL RESULTS; FINITE MIXTURE MODELS; FINITE MIXTURES; INFORMATIVE PRIORS; MEAN VALUES; NEGATIVE BINOMIAL; NEGATIVE BINOMIAL REGRESSION MODEL; NON-INFORMATIVE PRIOR; SAMPLE SIZES; SIMULATION RESULT; SIMULATION STUDIES; SMALL SAMPLE SIZE; SMALL SAMPLES; STATISTICAL MODELS; SUMMARY STATISTIC; TWO-COMPONENT; UNOBSERVED HETEROGENEITY;

BAYESIAN NETWORKS; DATA HANDLING; DISPERSIONS; HIGH ENERGY PHYSICS; REGRESSION ANALYSIS; SAMPLING; STATISTICS;

MIXTURES;

ARTICLE; BAYES THEOREM; BINOMIAL DISTRIBUTION; COMPUTER SIMULATION; EPIDEMIOLOGY; HUMAN; MONTE CARLO METHOD; STATISTICAL MODEL; STATISTICS; TRAFFIC ACCIDENT;

ACCIDENTS, TRAFFIC; BAYES THEOREM; BIAS (EPIDEMIOLOGY); BINOMIAL DISTRIBUTION; COMPUTER SIMULATION; HUMANS; MODELS, STATISTICAL; MONTE CARLO METHOD;

EID: 76049105420     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2009.11.002     Document Type: Article

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