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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/8235

Title: Discrete valued time series models for examining weather effects in daily accident counts
Authors: KARLIS, Dimitris
Sermaidis, G.J.
Issue Date: 2007
Citation: De Castillo et al. (Ed.) Proceedings of the 22th International Workshop on Statistical Modelling. p. 368-373.
Abstract: In this paper we aim at examining the effect of weather conditions in daily accident counts. In order to account for the serial correlation and the overdispersion present to the data, we make use of two models for discrete valued time series using covariate information. The models considered are the model of Zeger and the Integer Autoregressive model including covariates. Estimation procedures and possible extensions of the models are discussed. Data from 27 major cities roads in the Netherlands are examined. We make use of a meta-analysis approach in order to combine the effects retrieved for each site with site-specific covariate information.
URI: http://hdl.handle.net/1942/8235
ISBN: 978-84-690-5943-2
Category: C1
Type: Proceedings Paper
Appears in Collections: Research publications

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