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Feasible parameter regions for alternative discrete state space models

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  • Feigin, Paul D.
  • Gould, Phillip
  • Martin, Gael M.
  • Snyder, Ralph D.

Abstract

This paper provides a comparison of a parameter-driven and an observation-driven discrete state space model. The two models are shown to have non-overlapping feasible regions for dispersion and first-order autocorrelation, with the region for the parameter-driven model being much larger than that of the observation-driven model, as well as providing a much better representation of the empirical moments of observed count series.

Suggested Citation

  • Feigin, Paul D. & Gould, Phillip & Martin, Gael M. & Snyder, Ralph D., 2008. "Feasible parameter regions for alternative discrete state space models," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2963-2970, December.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:17:p:2963-2970
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    Cited by:

    1. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    2. Ralph D. Snyder & J. Keith Ord, 2009. "Exponential Smoothing and the Akaike Information Criterion," Monash Econometrics and Business Statistics Working Papers 4/09, Monash University, Department of Econometrics and Business Statistics.
    3. James W. Taylor, 2012. "Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing," Management Science, INFORMS, vol. 58(3), pages 534-549, March.

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