Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/13235
Title: Poisson mixture regression for Bayesian inference on large over-dispersed transportation origin-destination matrices
Authors: PERRAKIS, Konstantinos 
KARLIS, Dimitris 
COOLS, Mario 
JANSSENS, Davy 
WETS, Geert 
Issue Date: 2012
Source: 27th International Workshop on Statistical Modelling, Prague, Czech Republic, 16-20 July 2012
Abstract: 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.
Keywords: OD matrix; Poisson mixtures; Poisson-inverse Gaussian
Document URI: http://hdl.handle.net/1942/13235
Category: C2
Type: Conference Material
Appears in Collections:Research publications

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