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  1. F200 未来材料・システム研究所
  2. F200a 雑誌掲載論文
  3. 学術雑誌

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

http://hdl.handle.net/2237/00028292
http://hdl.handle.net/2237/00028292
807c5ad1-427a-457a-9065-e103d89040a8
名前 / ファイル ライセンス アクション
Manuscript.pdf Manuscript (573.2 kB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2018-06-11
タイトル
タイトル A multivariate heterogeneous-dispersion count model for asymmetric interdependent freeway crash types
言語 en
著者 Mothafer, Ghasak I.M.A.

× Mothafer, Ghasak I.M.A.

WEKO 78152

en Mothafer, Ghasak I.M.A.

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Yamamoto, Toshiyuki

× Yamamoto, Toshiyuki

WEKO 78153

en Yamamoto, Toshiyuki

Search repository
Shankar, Venkataraman N.

× Shankar, Venkataraman N.

WEKO 78154

en Shankar, Venkataraman N.

Search repository
アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利
言語 en
権利情報 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
抄録
内容記述 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. We apply these techniques to study the interdependence structure among four types of traffic crashes using three years (2005–2007) of cross-sectional crash data record for 274 multilane freeway segments in the State of Washington, USA. These four categories of crash types are the rear end; sideswipe; fixed objects and other crash types. The empirical results show a significant presence of unobserved heterogeneous dependency across these types of crashes. The results indicate the important role of unobserved heterogeneity in variance and covariance structure estimation. An important outcome of this result is that it can affect inference on the relative impact of roadway geometrics on crash occurrence. For example, we find that horizontal curve related parameters on freeway segments substantially increase the joint likelihood of rear-end, sideswipe, fixed objects and other crash types, when compared to the characteristics of vertical curves.
言語 en
内容記述タイプ Abstract
内容記述
内容記述 ファイル公開:2020-02-01
言語 ja
内容記述タイプ Other
出版者
言語 en
出版者 Elsevier
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ AM
出版タイプResource http://purl.org/coar/version/c_ab4af688f83e57aa
DOI
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1016/j.trb.2017.12.008
ISSN
収録物識別子タイプ PISSN
収録物識別子 0191-2615
書誌情報 en : Transportation Research Part B: Methodological

巻 108, p. 84-105, 発行日 2018-02-01
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