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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/5483

Title: An application of the Autoregressive Conditional Poisson (ACP) model
Authors: Holloway, J
Haines, L
Leask, K
Keywords: Autoregressive Conditional Poisson
ACP
Static poisson regression
Time series models
SASA 2010
Count data
Issue Date: Nov-2010
Publisher: SASA 2010
Citation: Holloway, J, Haines, L and Leask, K. 2010. An application of the Autoregressive Conditional Poisson (ACP) model. SASA 2010 Conference, University of Cape Town, Cape Town, November 2010
Series/Report no.: Workflow request;7667
Abstract: When modelling count data that comes in the form of a time series, the static Poisson regression and standard time series models are often not appropriate. A current study therefore involves the evaluation of several observation-driven and parameter-driven time series models for count data. In the observation-driven class of models, a fairly simple model is the Autoregressive Conditional Poisson (ACP) model. This presentation will describe the formulation of this model, together with the extension to the Double Autoregressive Conditional Poisson (DACP) model and also present some results of how these models compare to the static Poisson regression when modelling example data of cholera epidemics.
Description: SASA 2010 Conference, University of Cape Town, Cape Town, November 2010
URI: http://hdl.handle.net/10204/5483
Appears in Collections:Logistics and quantitative methods
General science, engineering & technology

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