American Statistical Association
New York City
Metropolitan Area Chapter

Mailman School of Public Health
Columbia University
Department of Biostatistics Colloquium



TIME SERIES THAT COUNT!

by

Professor William Dunsmuir
Department of Mathematics and Statistics
University of New South Wales
Sydney, Australia


Abstract

In recent years, there has been rapid development of applications, models and methods for modelling of discrete valued time series. Important areas of application arise from diverse application areas including public health, traffic safety, hospital management, panel survey data, high-frequency financial data modelling and forecasting inventory. These applications require consideration of binary counts, binomial counts, Poisson counts and negative binomial counts. The lecture will focus on regression modelling of time series of counts in which the impact of covariates is assessed. Like all regression modelling in time series the possibility of serial dependence has to be considered since if it is ignored inferences about covariates can be incorrect. Unlike continuous valued time series, detection of serial dependence in count time series is difficult and at this stage underdeveloped. In view of this, I will advocate a model based approach. Two broad classes of models, applicable to all types of count distribution mentioned above, will be reviewed and strengths and weaknesses (including computational) of the two will be compared. Illustration of the ideas will be made using examples from experience with the above areas of application. I will also show how the modelling ideas can be used to help in determining the properties of the missingness process in incompletely observed time series - this latter application will be discussed in the context of a pollution level time series that initiated some much earlier research in missing data methods for time series. The talk will be largely non-technical with the aim of exposing people, who are not experts in time series, to recent developments in this area. Some connections and differences with modelling longitudinal data will emerge in the talk.


Date: Thursday, October 16, 2008
Time: 4:00 - 5:00 P.M.
Location: Mailman School of Public Health
Department of Biostatistics
722 West 168th Street
Biostatistics Computer Lab
6th Floor - Room 656
New York, New York

RESERVATIONS ARE NOT REQUIRED

Refreshments will be served at 3:30 P.M. in the
Biostatistics Conference Room (R627).


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