Holloway, Jennifer PHaines, LLeask, K2012-01-122012-01-122010-11Holloway, 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 2010http://hdl.handle.net/10204/5483SASA 2010 Conference, University of Cape Town, Cape Town, November 2010When 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.enAutoregressive Conditional PoissonACPStatic poisson regressionTime series modelsSASA 2010Count dataConference PresentationHolloway, J. P., Haines, L., & Leask, K. (2010). An application of the Autoregressive Conditional Poisson (ACP) model. SASA 2010. http://hdl.handle.net/10204/5483Holloway, Jennifer P, L Haines, and K Leask. "An application of the Autoregressive Conditional Poisson (ACP) model." (2010): http://hdl.handle.net/10204/5483Holloway JP, Haines L, Leask K, An application of the Autoregressive Conditional Poisson (ACP) model; SASA 2010; 2010. http://hdl.handle.net/10204/5483 .TY - Conference Presentation AU - Holloway, Jennifer P AU - Haines, L AU - Leask, K AB - 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. DA - 2010-11 DB - ResearchSpace DP - CSIR KW - Autoregressive Conditional Poisson KW - ACP KW - Static poisson regression KW - Time series models KW - SASA 2010 KW - Count data LK - https://researchspace.csir.co.za PY - 2010 T1 - An application of the Autoregressive Conditional Poisson (ACP) model TI - An application of the Autoregressive Conditional Poisson (ACP) model UR - http://hdl.handle.net/10204/5483 ER -