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Weakly Stationary Processes and Their Spectral Measures

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Stationary Processes and Discrete Parameter Markov Processes

Part of the book series: Graduate Texts in Mathematics ((GTM,volume 293))

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Abstract

Stationary stochastic processes are analyzed at the level of their first and second order characteristics, mean and covariance, using Fourier methods.

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Notes

  1. 1.

    See BCPT, Chap. VI.

  2. 2.

    BCPT, p. 168.

  3. 3.

    See BCPT, p.110.

  4. 4.

    According to a celebrated Theorem 23.9 in Chapter 23, this also provides an example of a special type of associated statistical dependence.

  5. 5.

    Stationary (translation invariant) and self-similar phenomena are of rather widespread interest in the sciences, especially in connection with critical phenomena. Thus the stochastic models for such phenomena typically involve random measures and/or generalized functions.

  6. 6.

    See BCPT, p.119.

  7. 7.

    See BCPT, p. 112.

  8. 8.

    See Bhattacharya and Waymire (2021) or BCPT, p.180.

  9. 9.

    A metaphor for a stationary sequence is a process viewed as a data stream movie for which statistically it does not matter when one arrives at the theater. Time-reversibility permits it to also be run backward without changing the stochastic structure.

References

  • Bhattacharya R, Waymire E (2021) Random walk, Brownian motion, and martingales. Graduate text in mathematics. Springer, New York

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  • Brockwell P, Davis R (1991) Time series: theory and methods. Springer series in statistics. Springer, New York

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  • Grenander U (1981) Abstract inference. Wiley, New York

    MATH  Google Scholar 

  • Lévy P (1953) Random functions: general theory with special reference to Laplacian random functions (Vol. 1, No. 12). University of California Press

    Google Scholar 

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Bhattacharya, R., Waymire, E. (2022). Weakly Stationary Processes and Their Spectral Measures. In: Stationary Processes and Discrete Parameter Markov Processes. Graduate Texts in Mathematics, vol 293. Springer, Cham. https://doi.org/10.1007/978-3-031-00943-3_2

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