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This article is cited in 1 scientific paper (total in 1 paper)
Short Communications
Weak Convergence of a Certain Functional
V. M. Kruglov, G. N. Petrovskaya M. V. Lomonosov Moscow State University, Faculty of Computational Mathematics and Cybernetics
Abstract:
We consider the functional $T_n=(S_1^2+\dots+S_n^2)/(nV_n^2)$ derived from a sequence $\{X_n\}_{n\ge 1}$ of independent identically distributed random variables, where $S_k=X_1+\dots+X_k$, $V_n^2=X_1^2+\dots+X_n^2$. Let $G$ be the distribution function of the random variable $\int_{0}^{1}W^2(t)\,dt$, where $W(t)$, $t\in [0,1]$, is a Wiener process. We show that the distribution function $T_n$ weakly converges to $G$ as $n\to\infty$ if and only if the distribution function of the random variable $X_1$ belongs to the attraction domain of the normal law and $\mathbf{E}X_1=0$.
Keywords:
weak convergence, convergence in probability, random variable, distribution function.
Received: 05.02.2001
Citation:
V. M. Kruglov, G. N. Petrovskaya, “Weak Convergence of a Certain Functional”, Teor. Veroyatnost. i Primenen., 46:4 (2001), 779–784; Theory Probab. Appl., 46:4 (2002), 721–727
Linking options:
https://www.mathnet.ru/eng/tvp3824https://doi.org/10.4213/tvp3824 https://www.mathnet.ru/eng/tvp/v46/i4/p779
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