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Teoriya Veroyatnostei i ee Primeneniya, 2000, Volume 45, Issue 1, Pages 175–177
DOI: https://doi.org/10.4213/tvp331
(Mi tvp331)
 

Short Communications

An inequality for a multidimensional characteristic function

N. G. Gamkrelidzeab

a Gubkin Russian State University of Oil and Gas
b A. Razmadze Mathematical Institute, Georgian Academy of Sciences
Abstract: Let $\xi $ be a vector-valued random variable in $\mathbf{R}^s$ and a corresponding density function $p_\xi(x)$ be “close” to the “standard”normal density. Under this condition an inequality for a characteristic function is proved. The inequality obtained is of interest for the problem of a lower estimator of the rate of convergence in the local limit theorem for densities. An analogous inequality for a lattice distribution was investigated in [N. G. Gamkrelidze, Litovsk. Mat. Sb., 7 (1967), pp. 405–408 (in Russian)] and was given in [V. V. Petrov, Sums of Independent Random Variables, Springer-Verlag, Berlin, New York, 1975] and [Yu. V. Prohorov and Yu. A. Rozanov, Probability Theory: Basic Concepts, Limit Theorems, and Random Processes, Springer-Verlag, Berlin, New York, 1969].
Keywords: vector-valued random variable, density function, standard normal density, characteristic function, local limit theorem.
Received: 16.10.1999
English version:
Theory of Probability and its Applications, 2001, Volume 45, Issue 1, Pages 133–135
DOI: https://doi.org/10.1137/S0040585X97978117
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: N. G. Gamkrelidze, “An inequality for a multidimensional characteristic function”, Teor. Veroyatnost. i Primenen., 45:1 (2000), 175–177; Theory Probab. Appl., 45:1 (2001), 133–135
Citation in format AMSBIB
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\paper An inequality for a multidimensional characteristic function
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\pages 175--177
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\transl
\jour Theory Probab. Appl.
\yr 2001
\vol 45
\issue 1
\pages 133--135
\crossref{https://doi.org/10.1137/S0040585X97978117}
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  • https://www.mathnet.ru/eng/tvp/v45/i1/p175
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    Теория вероятностей и ее применения Theory of Probability and its Applications
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