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 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Perrakis_etal_IWSM.pdf | Conference material | 120.81 kB | Adobe PDF | View/Open |
Page view(s)
24
checked on Jul 15, 2022
Download(s)
8
checked on Jul 15, 2022
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.