Observation‐driven models for Poisson counts

This paper is concerned with a general class of observation‐driven models for time series of counts whose conditional distributions given past observations and explanatory variables follow a Poisson distribution. These models provide a flexible framework for modelling a wide range of dependence stru...

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Veröffentlicht in:	Biometrika 2003-12, Vol.90 (4), p.777-790
Hauptverfasser:	Davis, Richard A., Dunsmuir, William T. M., Streett, Sarah B.
Format:	Artikel
Sprache:	eng
Schlagworte:	Asthma Asthma hospitalisation Autoregressive moving average Ergodic theory Exact sciences and technology Inference from stochastic processes time series analysis Linear inference, regression Mathematics Maximum likelihood estimation Maximum likelihood estimators Modeling Observation‐driven model Parametric models Poisson‐valued time series Probability and statistics Random variables Regression analysis Sciences and techniques of general use Statistics Time series Time series models
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