This article is cited in 3 papers

Multidimensional limit theorems for large deviations

L. V. Osipov

Leningrad State University

Abstract: Let $S_n=X^{(1)}+\dots+X^{(n)}$ be a sum of independent identically distributed random vectors in $R^k$ and let $\Phi$ be the standard normal distribution in $R^k$. Conditions upon distribution of $X^{(1)}$ are given under which
$$ \mathbf P\{S_n/\sqrt n\in A_n\}=\Phi(A_n)(1+o(1)),\quad n\to\infty, $$
uniformly in sequences of Borel sets $\{A_n\}$ such that $\Phi(A_n)\ge\Phi(x\colon|x|>\Lambda(n))$ where $\Lambda(z)\uparrow\infty$ is a function satisfying condition (8). In Theorems 1 and 2, we consider the case $\Lambda(z)=bz^\alpha$, $b>0$, $0<\alpha<1/2$.

Received: 19.04.1972

 English version: Theory of Probability and its Applications, 1975, 20:1, 38–56

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