Analysis of nonstationary modulated time series with applications to oceanographic flow measurements

@inproceedings{Guillaumin2016AnalysisON,
  title={Analysis of nonstationary modulated time series with applications to oceanographic flow measurements},
  author={Arthur P. Guillaumin and Adam M. Sykulski and Sofia C. Olhede and Jeffrey J. Early and Jonathan M. Lilly},
  year={2016}
}
  • Arthur P. Guillaumin, Adam M. Sykulski, +2 authors Jonathan M. Lilly
  • Published 2016
  • Mathematics, Physics
  • We extend the concept of a modulated nonstationary process to account for rapidly time-evolving correlation structure. This correlation varies sufficiently fast to make existing theory for nonstationary processes not applicable. The rapid variation in the correlations challenges state-of-the-art methods to make inferences. Even for stationary processes, exact inference in the time domain is often not computa- tionally viable. A well-established and fast approximation, known as the Whittle… CONTINUE READING

    Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

    Figures and Tables from this paper.

    Citations

    Publications citing this paper.
    SHOWING 1-3 OF 3 CITATIONS

    Quasi-likelihood inference for modulated non-stationary time series

    VIEW 4 EXCERPTS
    CITES BACKGROUND & METHODS

    Prediction in locally stationary time series

    VIEW 5 EXCERPTS
    CITES BACKGROUND, RESULTS & METHODS
    HIGHLY INFLUENCED

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 35 REFERENCES

    A Widely Linear Complex Autoregressive Process of Order One

    VIEW 13 EXCERPTS

    Mental states as macrostates emerging from brain electrical dynamics.

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL