AStA Advances in Statistical Analysis

, Volume 95, Issue 1, pp 59–91

Useful models for time series of counts or simply wrong ones?

Original Paper

DOI: 10.1007/s10182-010-0139-9

Cite this article as:
Jung, R.C. & Tremayne, A.R. AStA Adv Stat Anal (2011) 95: 59. doi:10.1007/s10182-010-0139-9

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.

Keywords

Count time seriesParameter-drivenObservation-drivenAutocorrelationOverdispersionDiagnostics

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Staatswissenschaftliche FakultätUniversität ErfurtErfurtGermany
  2. 2.School of EconomicsUniversity of New South WalesSydneyAustralia
  3. 3.University of YorkYorkUK