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Abstract Details
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Activity Number:
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317
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Type:
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Invited
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Date/Time:
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Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #300125 |
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Title:
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Autoregressive Models for Count Time Series
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Author(s):
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Konstantinos Fokianos*+
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Companies:
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University of Cyprus
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Address:
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Math and Stat Department, Nicosia, 1678, Cyprus
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Keywords:
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estimation ;
prediction ;
stationarity ;
autocorrelation function ;
covariates ;
modeling
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Abstract:
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Count time series are observed in diverse applications, for instance consider the number of transaction per minute of some stock, or the monthly number of people with a certain disease, and so on. For the analysis of these data, there has been developed a number of models based either on thinning operator or on GLM framework. We will be examining the second class of models which include a feedback mechanism. Such models are expected, in general, to be more parsimonious, pretty much as is the case of GARCH models. It is important therefore to study their statistical properties and develop algorithms for estimation. In particular we will be discussing some multivariate generalizations of previously established models in the literature.
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Authors who are presenting talks have a * after their name.
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