His scientific interests lie mostly in Statistics, Transport engineering, Econometrics, Poisson distribution and Statistical model. His Statistics study is mostly concerned with Count data, Overdispersion, Sample size determination and Regression analysis. His research integrates issues of Predictive modelling and Accident in his study of Transport engineering.
The various areas that Dominique Lord examines in his Econometrics study include Mixed logit and Multinomial logistic regression. Dominique Lord specializes in Poisson distribution, namely Negative binomial distribution. His Statistical model study frequently links to related topics such as Bayes' theorem.
Dominique Lord spends much of his time researching Transport engineering, Statistics, Negative binomial distribution, Econometrics and Regression analysis. The Transport engineering study combines topics in areas such as Crash data and Data collection. His work on Simulation expands to the thematically related Statistics.
His research in Negative binomial distribution tackles topics such as Mathematical model which are related to areas like Covariate. His Econometrics research includes themes of Estimator, Statistical dispersion, Bayes' theorem and Confidence interval. His Regression analysis research includes elements of Mixture model, Poisson regression and Linear regression.
The scientist’s investigation covers issues in Statistics, Transport engineering, Negative binomial distribution, Crash data and Regression analysis. His Statistics study combines topics from a wide range of disciplines, such as Major injury, Crash severity, Poisson regression and Econometrics. His study in Econometrics is interdisciplinary in nature, drawing from both Variation, Data quality, Generalized linear model and Bayesian probability.
The Annual average daily traffic research Dominique Lord does as part of his general Transport engineering study is frequently linked to other disciplines of science, such as Intersection, Technical report and Hazard mitigation, therefore creating a link between diverse domains of science. His Negative binomial distribution study combines topics in areas such as Probability distribution, Count data and Statistical dispersion. He regularly ties together related areas like Poisson distribution in his Regression analysis studies.
His primary areas of investigation include Negative binomial distribution, Econometrics, Statistics, Regression analysis and Crash data. His Negative binomial distribution research includes elements of Probability distribution, Count data and Statistical dispersion. His Econometrics research is multidisciplinary, incorporating elements of Generalized linear model and Bayesian probability.
His Regression analysis study frequently draws connections between adjacent fields such as Poisson distribution. His work carried out in the field of Poisson distribution brings together such families of science as Linear regression, Deviance information criterion, Bayesian inference, Bayes' theorem and Zero-inflated model. As a member of one scientific family, Dominique Lord mostly works in the field of Crash data, focusing on Poisson lognormal and, on occasion, Model selection.
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The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives
Dominique Lord;Fred L. Mannering.
Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory
Dominique Lord;Simon P. Washington;John N. Ivan.
Accident Analysis & Prevention (2005)
The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives.
Peter T. Savolainen;Fred L. Mannering;Dominique Lord;Mohammed Abdul Quddus.
MODELING TRAFFIC CRASH-FLOW RELATIONSHIPS FOR INTERSECTIONS: DISPERSION PARAMETER, FUNCTIONAL FORM, AND BAYES VERSUS EMPIRICAL BAYES METHODS
Shaw-Pin Miaou;Dominique Lord.
Transportation Research Record (2003)
Modeling motor vehicle crashes using Poisson-gamma models: examining the effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter.
Accident Analysis & Prevention (2006)
Safety Effect of Roundabout Conversions in the United States: Empirical Bayes Observational Before-After Study
Bhagwant N. Persaud;Richard A. Retting;Per E. Garder;Dominique Lord.
Multivariate Poisson-Lognormal Models for Jointly Modeling Crash Frequency by Severity
Eun Sug Park;Dominique Lord.
Transportation Research Record (2007)
Predicting motor vehicle crashes using Support Vector Machine models.
Xiansheng Li;Dominique Lord;Yunlong Zhang;Yuanchang Xie.
Accident Analysis & Prevention (2008)
Accident Prediction Models With and Without Trend: Application of the Generalized Estimating Equations Procedure
Dominique Lord;Bhagwant N. Persaud.
Comparing Three Commonly Used Crash Severity Models on Sample Size Requirements: Multinomial Logit, Ordered Probit, and Mixed Logit Models
Fan Ye;Dominique Lord.
Analytic Methods in Accident Research (2014)
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