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Convergence conditions for variance estimator of Gaussian stationary stochastic processes in Orlicz spaces

  • Applied Topics in Control Theory, Mathematical Cybernetics, and Statistics
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Abstract

Conditions are derived ensuring convergence of the variance estimator of a Gaussian stationary stochastic process in Orlicz space norm. Confidence intervals are constructed.

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References

  1. A. M. Yaglom, Correlation Theory of Stationary Random Functions [in Russian], Leningrad (1981).

  2. M. A. Krasnosel'skii and Ya. B. Rutitskii, Convex Functions and Orlicz Spaces [in Russian], Moscow (1958).

  3. E. P. Besklinskaya and Yu. V. Kozachenko, “Convergence in Orlicz space norms and Levy-Baxter theorems,” Teor. Veroyatn. Mat. Stat., No. 35, 3–6 (1986).

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Authors and Affiliations

  1. Kiev University, Ukraine

    A. I. Stadnik

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  1. A. I. Stadnik
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Additional information

Translated from Vychislitel'naya i Prikladnaya Matematika, No. 73, pp. 113–116, 1992.

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Stadnik, A.I. Convergence conditions for variance estimator of Gaussian stationary stochastic processes in Orlicz spaces. J Math Sci 71, 2716–2718 (1994). https://doi.org/10.1007/BF02114050

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  • DOI: https://doi.org/10.1007/BF02114050

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