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Trend analysis of time series for measurements at random moments of time

  • Mathematical Processing of Physics Experimental Data
  • Published:
Russian Physics Journal Aims and scope

Abstract

Trend identification algorithms are suggested and investigated for time series, when the measurement moments form a Poisson or recurrent sequence of events. The case is investigated in which only the sequence of occurrence of the moments of measurement is known.

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References

  1. T. W. Anderson, The Statistical Analysis of Time Series, Wiley, New York (1971).

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  2. B. V. Gnedenko and I. N. Kovalenko, Introduction to the Theory of Mass Production [in Russian], Nauka, Moscow (1987).

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  3. M. G. Kendall and A. Stuart, The Advanced Theory of Statistics, 4th ed., MacMillan, New York (1977).

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  4. T. W. Anderson, An Introduction to Multivariate Statistical Analysis, Wiley, New York (1958).

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Authors and Affiliations

  1. Ship and Anchor Branch of the Tomsk Pedagogical Institute, Russia

    F. F. Idrisov

Authors
  1. F. F. Idrisov
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Additional information

Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Fizika, No. 3, pp. 3–10, March, 1995.

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Idrisov, F.F. Trend analysis of time series for measurements at random moments of time. Russ Phys J 38, 217–224 (1995). https://doi.org/10.1007/BF00559463

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  • DOI: https://doi.org/10.1007/BF00559463

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