Some recent progress in count time series

Abstract

We review some regression models for the analysis of count time series. These models have been the focus of several investigations over the last years, but only recently simple conditions for stationarity and ergodicity were worked out in detail. This advancement makes possible the development of the maximum-likelihood estimation theory under minimal assumptions.

Keywords:

• autocorrelation
• covariates
• ergodicity
• generalized linear models
• perturbation
• prediction
• stationarity
• volatility

Acknowledgements

Special thanks to P. Doukhan for inviting me to contribute to this volume. Constructive comments from two reviewers improved the presentation of an earlier version.