A multivariate heterogeneous-dispersion count model for asymmetric interdependent freeway crash types

Ghasak I.M.A. Mothafer, Toshiyuki Yamamoto and Venkataraman N. Shankar

Transportation Research Part B: Methodological, 2018, vol. 108, issue C, 84-105

Abstract: A multivariate count model is developed by introducing a simple and practical formula. The formulation begins with a modification of the standard ordered response model to adopt the count outcomes nature. This modification is accomplished by introducing a non-linear asymmetric interdependence structure among the error terms using the copula-based model. To avoid simulation maximum-likelihood for evaluating the multi-outcome density, we utilize the composite marginal likelihood (CML) approach. The proposed copula-based model with the CML approach allows for asymmetric (tail) dependency without a need for a simulation mechanism. Non-parametric graphical techniques with the empirical copula as well as conventional goodness-of-fit statistics are utilized to guide copula selection. In addition, unobserved heterogeneity across observations is also addressed through a heterogeneous dispersion parameter in the proposed model. The heterogeneous dispersion parameter model is a suitable alternative to random parameter count models in that captures heterogeneity in variance, while allowing for closed form while the latter needs numerical integration or simulation.

Keywords: Multivariate count data; Copula; Composite marginal likelihood; Crash type correlations; Variance-covariance structure; Heterogeneous dispersion (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.trb.2017.12.008

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