Useful models for time series of counts or simply wrong ones? |
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Authors: | Robert C Jung A R Tremayne |
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Institution: | (1) Sustainable Technology Division, Sustainable Environments Branch, U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 26 West Martin Luther King Drive, Cincinnati, OH 45268, USA;(2) Economic and Industry Analysis Division, U.S. Department of Transportation, Volpe National Transportation Systems Center, 55 Broadway, Cambridge, MA 02142-1093, USA |
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Abstract: | There has been a considerable and growing interest in low integer-valued time series data leading to a diversification of
modelling approaches. In addition to static regression models, both observation-driven and parameter-driven models are considered
here. We compare and contrast a variety of time series models for counts using two very different data sets as a testbed.
A range of diagnostic devices is employed to help inform model adequacy. Special attention is paid to dynamic structure and
underlying distributional assumptions including associated dispersion properties. Competing models show attractive features,
but overall no one modelling approach is seen to dominate. |
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Keywords: | |
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