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Teoriya Veroyatnostei i ee Primeneniya, 1969, Volume 14, Issue 2, Pages 319–326 (Mi tvp1177)  

This article is cited in 22 scientific papers (total in 22 papers)

Short Communications

Some theorems of the strong-law-of-large-numbers type

V. N. Tutubalin

Moscow
Abstract: Let $G$ be the $SL(m)$, $U$ the $S\mathscr O(m)$, $\Gamma$ the diagonal subgroup of $U$ and $X=U/\Gamma$. Consider a sequence $g_1,\dots,g_n,\dots$ of independent identically distributed random elements of $G$. Let
$$ g(n)=g_1g_2\dots g_n=x(n)d(n)u(n), $$
where $x(n)\in X$, $u(n)\in U$ and $d(n)=\operatorname{diag}(e^{t_1(n)},\dots,e^{t_m(n)})$, $t_1(n)<\dots<t_m(n)$. Under some condition on the distribution of $g_i$ the following theorems are proved:
1) there exist real numbers $a_1<a_2<\dots<a_m$ such that, with probability 1,
$$ \frac1nt_k(n)\to a_k,\quad k=1,\dots,m; $$

2) with probability 1, $x(n)\to x(\infty)$, where $x(\infty)$ is a random element of $X$.
Received: 27.02.1968
English version:
Theory of Probability and its Applications, 1969, Volume 14, Issue 2, Pages 313–319
DOI: https://doi.org/10.1137/1114039
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: V. N. Tutubalin, “Some theorems of the strong-law-of-large-numbers type”, Teor. Veroyatnost. i Primenen., 14:2 (1969), 319–326; Theory Probab. Appl., 14:2 (1969), 313–319
Citation in format AMSBIB
\Bibitem{Tut69}
\by V.~N.~Tutubalin
\paper Some theorems of the strong-law-of-large-numbers type
\jour Teor. Veroyatnost. i Primenen.
\yr 1969
\vol 14
\issue 2
\pages 319--326
\mathnet{http://mi.mathnet.ru/tvp1177}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=248895}
\zmath{https://zbmath.org/?q=an:0196.20904|0191.47603}
\transl
\jour Theory Probab. Appl.
\yr 1969
\vol 14
\issue 2
\pages 313--319
\crossref{https://doi.org/10.1137/1114039}
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  • https://www.mathnet.ru/eng/tvp/v14/i2/p319
  • This publication is cited in the following 22 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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