Modeling Time Series Count Data: A State-Space Approach toEvent Counts

Modeling Time Series Count Data: A State-Space Approach toEvent Counts (1998)

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by Patrick T. Br , John T. Williams , Benjamin Fordham

BibTeX

@MISC{Br98modelingtime,
    author = {Patrick T. Br and John T. Williams and Benjamin Fordham},
    title = {Modeling Time Series Count Data: A State-Space Approach toEvent Counts},
    year = {1998}
}

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Abstract

Time series count data is prevalent in political science. We argue that political scientists should employ time series methods to analyze time series count data. A simple state-space model is presented that extends the Kalman lter to count data. The properties of this model are outlined and further evaluated by a Monte Carlo study. Wethen show howtime series of counts present special problems by turning to two replications: the number of hospital deaths that are the subject of a recent criminal court case, and Pollins (1996) MIDs data from international relations.

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