Corpus ID: 88518887

Theory and Inference for a Class of Observation-driven Models with Application to Time Series of Counts

@article{Davis2012TheoryAI,
  title={Theory and Inference for a Class of Observation-driven Models with Application to Time Series of Counts},
  author={Richard A. Davis and Heng Liu},
  journal={arXiv: Statistics Theory},
  year={2012}
}
This paper studies theory and inference related to a class of time series models that incorporates nonlinear dynamics. It is assumed that the observations follow a one-parameter exponential family of distributions given an accompanying process that evolves as a function of lagged observations. We employ an iterated random function approach and a special coupling technique to show that, under suitable conditions on the parameter space, the conditional mean process is a geometric moment… Expand
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