• Title/Summary/Keyword: Weighted i.i.d. random variables

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Almost sure convergence for weighted sums of I.I.D. random variables (II)

  • Sung, Soo-Hak
    • Bulletin of the Korean Mathematical Society
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    • v.33 no.3
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    • pp.419-425
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    • 1996
  • Let ${X, X_n, n \geq 1}$ be a sequence of independent and identically distributed(i.i.d) random variables with EX = 0 and $E$\mid$X$\mid$^p < \infty$ for some $p \geq 1$. Let ${a_{ni}, 1 \leq i \leq n, n \geq 1}$ be a triangular arrary of constants. The almost sure(a.s) convergence of weighted sums $\sum_{i=1}^{n} a_{ni}X_i$ can be founded in Choi and Sung[1], Chow[2], Chow and Lai[3], Li et al. [4], Stout[6], Sung[8], Teicher[9], and Thrum[10].

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STRONG STABILITY OF A TYPE OF JAMISON WEIGHTED SUMS FOR END RANDOM VARIABLES

  • Yan, Jigao
    • Journal of the Korean Mathematical Society
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    • v.54 no.3
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    • pp.897-907
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    • 2017
  • In this paper, we consider the strong stability of a type of Jamison weighted sums, which not only extend the corresponding result of Jamison etc. [13] from i.i.d. case to END random variables, but also obtain the necessary and sufficient results. As an important consequence, we present the result of SLLN as that of i.i.d. case.

On the Almost Certain Rate of Convergence of Series of Independent Random Variables

  • Nam, Eun-Woo;Andrew Rosalsky
    • Journal of the Korean Statistical Society
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    • v.24 no.1
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    • pp.91-109
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    • 1995
  • The rate of convergence to a random variable S for an almost certainly convergent series $S_n = \sum^n_{j=1} X_j$ of independent random variables is studied in this paper. More specifically, when $S_n$ converges to S almost certainly, the tail series $T_n = \sum^{\infty}_{j=n} X_j$ is a well-defined sequence of random variable with $T_n \to 0$ a.c. Various sets of conditions are provided so that for a given numerical sequence $0 < b_n = o(1)$, the tail series strong law of large numbers $b^{-1}_n T_n \to 0$ a.c. holds. Moreover, these results are specialized to the case of the weighted i.i.d. random varialbes. Finally, example are provided and an open problem is posed.

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STRONG LAWS FOR WEIGHTED SUMS OF I.I.D. RANDOM VARIABLES (II)

  • Sung, Soo-Hak
    • Bulletin of the Korean Mathematical Society
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    • v.39 no.4
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    • pp.607-615
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    • 2002
  • Let (X, $X_{n}$, n$\geq$1) be a sequence of i.i.d. random variables and { $a_{ni}$ , 1$\leq$i$\leq$n, n$\geq$1} be an array of constants. Let ø($\chi$) be a positive increasing function on (0, $\infty$) satisfying ø($\chi$) ↑ $\infty$ and ø(C$\chi$) = O(ø($\chi$)) for any C > 0. When EX = 0 and E[ø(|X|)]〈$\infty$, some conditions on ø and { $a_{ni}$ } are given under which (equation omitted).).

ON COMPLETE CONVERGENCE FOR WEIGHTED SUMS OF I.I.D. RANDOM VARIABLES WITH APPLICATION TO MOVING AVERAGE PROCESSES

  • Sung, Soo-Hak
    • Bulletin of the Korean Mathematical Society
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    • v.46 no.4
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    • pp.617-626
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    • 2009
  • Let {$Y_i$,-$\infty$ < i < $\infty$} be a doubly infinite sequence of i.i.d. random variables with E|$Y_1$| < $\infty$, {$a_{ni}$,-$\infty$ < i < $\infty$ n $\geq$ 1} an array of real numbers. Under some conditions on {$a_{ni}$}, we obtain necessary and sufficient conditions for $\sum\;_{n=1}^{\infty}\frac{1}{n}P(|\sum\;_{i=-\infty}^{\infty}a_{ni}(Y_i-EY_i)|$>$n{\epsilon})$<{\infty}$. We examine whether the result of Spitzer [11] holds for the moving average process, and give a partial solution.

STRONG LAWS FOR WEIGHTED SUMS OF I.I.D. RANDOM VARIABLES

  • Cai, Guang-Hui
    • Communications of the Korean Mathematical Society
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    • v.21 no.4
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    • pp.771-778
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    • 2006
  • Strong laws are established for linear statistics that are weighted sums of a random sample. We show extensions of the Marcinkiewicz-Zygmund strong laws under certain moment conditions on both the weights and the distribution. The result obtained extends and sharpens the result of Sung ([12]).

ALMOST SURE CONVERGENCE FOR WEIGHTED SUMS OF NA RANDOM VARIABLES

  • BAEK J. I.;NIU S. L.;LIM P. K.;AHN Y. Y.;CHUNG S. M.
    • Journal of the Korean Statistical Society
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    • v.34 no.4
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    • pp.263-272
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    • 2005
  • Let {$X_n,\;n{\ge}1$} be a sequence of negatively associated random variables which are dominated randomly by another random variable. We discuss the limit properties of weighted sums ${\Sigma}^n_{i=1}a_{ni}X_i$ under some appropriate conditions, where {$a_{ni},\;1{\le}\;i\;{\le}\;n,\;n\;{\ge}\;1$} is an array of constants. As corollary, the results of Bai and Cheng (2000) and Sung (2001) are extended from the i.i.d. case to not necessarily identically distributed negatively associated setting. The corresponding results of Chow and Lai (1973) also are extended.

ON ALMOST SURE CONVERGENCE FOR WEIGHTED SUMS OF LNQD RANDOM VARIABLES

  • Choi, Jeong-Yeol;Kim, So-Youn;Baek, Jong-Il
    • Honam Mathematical Journal
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    • v.34 no.2
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    • pp.241-252
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    • 2012
  • Let $\{X_{ni},\;1{\leq}i{\leq}n,\;n{\geq}1\}$ be a sequence of LNQD which are dominated randomly by another random variable X. We obtain the complete convergence and almost sure convergence of weighted sums ${\sum}^n_{i=1}a_{ni}X_{ni}$ for LNQD by using a new exponential inequality, where $\{a_{ni},\;1{\leq}i{\leq}n,\;n{\geq}1\}$ is an array of constants. As corollary, the results of some authors are extended from i.i.d. case to not necessarily identically LNQD case.