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Z-Process Method for Change Point Problems in Time Series

In: Research Papers in Statistical Inference for Time Series and Related Models

Author

Listed:
  • Ilia Negri

    (University of Calabria)

Abstract

Z-process method was introduced as a general unified approach based on partial estimation functions to construct a statistical test in change point problems not only for ergodic models but also for some non-ergodic models where the Fisher information matrix is random. In this paper, we consider the problem of testing for parameter changes in time series models based on this Z-process method. As an example, we consider the parameter change problem in some linear time series models. Some possibilities for nonlinear models are also discussed.

Suggested Citation

  • Ilia Negri, 2023. "Z-Process Method for Change Point Problems in Time Series," Springer Books, in: Yan Liu & Junichi Hirukawa & Yoshihide Kakizawa (ed.), Research Papers in Statistical Inference for Time Series and Related Models, chapter 0, pages 381-388, Springer.
    • Handle: RePEc:spr:sprchp:978-981-99-0803-5_15
    DOI: 10.1007/978-981-99-0803-5_15
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