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Teoriya Veroyatnostei i ee Primeneniya, 1974, Volume 19, Issue 2, Pages 308–318 (Mi tvp2853)  

This article is cited in 5 scientific papers (total in 5 papers)

On infinitely divisible distributions

V. V. Yurinskii

Moscow
Full-text PDF (512 kB) Citations (5)
Abstract: Let $F$ be a $\sigma$-finite measure with the property (3), § 2, in a separable Banach space $\mathscr B$. $F$ belongs to $\mathfrak G$ iff the infinitely divisible distributions in $\mathscr B$ with the ch.f.
$$ \exp\biggl\{2\int_{|x|\ge\varepsilon}\cos(\langle t,x\rangle-1)F(dx)\biggr\} $$
have a weak limit $e(\widetilde F)$ as $\varepsilon\to0$.
If $F$ of class $\mathfrak G$ is concentrated in a bounded set,
$$ \int\exp(\gamma|x|)e(F)(dx) $$
is finite for some $\gamma>0$; $\int\langle t,x\rangle^2F(dx)\le C|t|^2$.
For $\mathscr B=l_p$, $p\ge2$, this leads to a characterization of $\mathfrak G$ (Theorem 3).
In the general case, condition
$$ \int_{|x|\le1}|x|F(dx) $$
is shown to imply $F\in\mathfrak G$.
Received: 12.06.1973
English version:
Theory of Probability and its Applications, 1975, Volume 19, Issue 2, Pages 297–308
DOI: https://doi.org/10.1137/1119035
Bibliographic databases:
Language: Russian
Citation: V. V. Yurinskii, “On infinitely divisible distributions”, Teor. Veroyatnost. i Primenen., 19:2 (1974), 308–318; Theory Probab. Appl., 19:2 (1975), 297–308
Citation in format AMSBIB
\Bibitem{Yur74}
\by V.~V.~Yurinskii
\paper On infinitely divisible distributions
\jour Teor. Veroyatnost. i Primenen.
\yr 1974
\vol 19
\issue 2
\pages 308--318
\mathnet{http://mi.mathnet.ru/tvp2853}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=1211168}
\zmath{https://zbmath.org/?q=an:0309.60006}
\transl
\jour Theory Probab. Appl.
\yr 1975
\vol 19
\issue 2
\pages 297--308
\crossref{https://doi.org/10.1137/1119035}
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  • https://www.mathnet.ru/eng/tvp/v19/i2/p308
    Erratum
    This publication is cited in the following 5 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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    Теория вероятностей и ее применения Theory of Probability and its Applications
     
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