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Poisson mixture regression for Bayesian inference on large over-dispersed transportation origin-destination matrices
Perrakis, Konstantinos; Karlis, Dimitris; Cools, Mario et al.
2012In 27th International Workshop on Statistical Modelling
Peer reviewed
 

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Keywords :
OD matrix; Poisson mixtures; Poisson-inverse Gaussian
Abstract :
[en] We propose a statistical modeling approach as a viable alternative to traditional transportation models concerning inference on origin-destination (OD) matrices. To this end we utilize Poisson mixtures in order to model a large over-dispersed OD matrix derived from the 2001 Belgian travel census. Bayesian methods are using a novel Poisson-inverse Gaussian model. As shown the model has desirable attributes both in its marginal and in its hierarchical form.
Disciplines :
Special economic topics (health, labor, transportation...)
Civil engineering
Author, co-author :
Perrakis, Konstantinos
Karlis, Dimitris
Cools, Mario  ;  Université de Liège - ULiège > Département ArGEnCo > Transports et mobilité
Janssens, Davy
Wets, Geert
Language :
English
Title :
Poisson mixture regression for Bayesian inference on large over-dispersed transportation origin-destination matrices
Publication date :
2012
Event name :
27th International Workshop on Statistical Modelling, Prague, Czech Republic
Event date :
16-20 July 2012
Main work title :
27th International Workshop on Statistical Modelling
Peer reviewed :
Peer reviewed
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since 03 February 2020

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