Equivalence between tails, Grand Lebesgue Spaces and Orlicz norms for random variables without Kramer's condition

Автор(и)

  • Yu. Kozachenko Taras Shevchenko National University of Kyiv, Kiev, Ukraine https://orcid.org/0000-0001-6996-8368
  • E. Ostrovsky Bar-Ilan University, 59200, Ramat Gan, Israel
  • L. Sirota Bar-Ilan University, 59200, Ramat Gan, Israel

DOI:

https://doi.org/10.17721/1812-5409.2018/4.3

Анотація

We offer in this paper the non-asymptotical pairwise bilateral exact up to multiplicative constants interrelations between the tail behavior, moments (Grand Lebesgue Spaces) norm and Orlicz’s norm for random variables (r.v.), which does not satisfy in general case the Kramer’s condition.

Key words: Random variable and random vector (r.v.), saddle-point method, tail of distribution, moments, Lebesgue-Riesz, Orlicz and Grand Lebesgue Spaces (GLS); slowly varying functions, Young-Fenchel transform, theorem and inequality of Fenchel-Moreau, Young-Orlicz function, Markov-Chernov’s estimate, non-asymptotical estimates, Kramer’s condition.

Pages of the article in the issue: 20 - 29

Language of the article: English

Біографії авторів

  • Yu. Kozachenko, Taras Shevchenko National University of Kyiv, Kiev, Ukraine

    Department of Probability Theory, Statistics
    and Actuarial Mathematics, Prof.

  • E. Ostrovsky, Bar-Ilan University, 59200, Ramat Gan, Israel
    Department of Mathematics
  • L. Sirota, Bar-Ilan University, 59200, Ramat Gan, Israel
    Department of Mathematics

Посилання

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Завантаження

Опубліковано

27.01.2020

Номер

Розділ

Алгебра, геометрія та теорія ймовірностей

Як цитувати

Kozachenko, Y., Ostrovsky, E., & Sirota, L. (2020). Equivalence between tails, Grand Lebesgue Spaces and Orlicz norms for random variables without Kramer’s condition. Вісник Київського національного університету імені Тараса Шевченка. Фізико-математичні науки, 4, 20-29. https://doi.org/10.17721/1812-5409.2018/4.3