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Time Series Recursions and Self-Tuning Control

In: Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface

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  • Victor Solo

    (Harvard University)

Abstract

Recursive estimates are estimates (of parameters in a time series model) that are computed in a sequential fashion (i.e. updated quickly as new observations become available). The uses of such “real” time parameter estimators include real-time forecasting and self-tuning control. Here it is shown how “real” time parameter estimators can be constructed for time series models; also an heuristic discussion of their convergence behavior is given. The analysis and synthesis of self-tuning controllers is also discussed.

Suggested Citation

  • Victor Solo, 1981. "Time Series Recursions and Self-Tuning Control," Springer Books, in: William F. Eddy (ed.), Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface, pages 178-184, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4613-9464-8_26
    DOI: 10.1007/978-1-4613-9464-8_26
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