• Title/Summary/Keyword: pairwise independent random variables

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THE STRONG LAWS OF LARGE NUMBERS FOR WEIGHTED SUMS OF PAIRWISE QUADRANT DEPENDENT RANDOM VARIABLES

  • Kim, Tae-Sung;Baek, Jong-Il
    • Journal of the Korean Mathematical Society
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    • v.36 no.1
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    • pp.37-49
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    • 1999
  • We derive the almost sure convergence for weighted sums of random variables which are either pairwise positive quadrant dependent or pairwise positive quadrant dependent or pairwise negative quadrant dependent and then apply this result to obtain the almost sure convergence of weighted averages. e also extend some results on the strong law of large numbers for pairwise independent identically distributed random variables established in Petrov to the weighted sums of pairwise negative quadrant dependent random variables.

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SLIN FOR WEIGHTED SUMS OF STOCHASTICALLY DOMINATED PAIRWISE INDEPENDENT RANDOM VARIABLES

  • Sung, Soo-Hak
    • Communications of the Korean Mathematical Society
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    • v.13 no.2
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    • pp.377-384
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    • 1998
  • Let ${X_n,n \geq 1}$ be a sequence of stochatically dominated pairwise independent random variables. Let ${a_n, n \geq 1}$ and ${b_n, n \geq 1}$ be seqence of constants such that $a_n \neq 0$ and $0 < b_n \uparrow \infty$. A strong law large numbers of the form $\sum^{n}_{j=1}{a_j X_i//b_n \to 0$ almost surely is obtained.

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SLLN for Pairwise Independent Random Variables (쌍별독립인 확률변수에 대한 대수의 강법칙)

  • Sung, Soo-Hak
    • The Journal of Natural Sciences
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    • v.11 no.1
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    • pp.15-17
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    • 1999
  • Let {f(n)} be an increasing sequence such that f(n)>0 for each n and f(n)$\rightarrow$$\infty$. Let {X$_n$,n$\geq1$} be a sequence of pairwise independent random variables. In this paper we give sufficient conditions on {X$_n$,n$\geq1$} such that $sum_{i=1}^n$(X$_i$-EX$_i$)/f(n) converges to zero almost surely.

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EXACT SEQUENCES FOR SUMS OF PAIRWISE I.I.D. RANDOM VARIABLES

  • Hong, Dug-Hun;Park, Jin-Myung
    • Bulletin of the Korean Mathematical Society
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    • v.30 no.2
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    • pp.167-170
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    • 1993
  • In this paper, X, X$_{1}$, X$_{2}$, .. will denote any sequence of pairwise independent random variables with common distribution, and b$_{1}$, b$_{2}$.. will denote any sequence of constants. Using Chung [2, Theorem 4.2.5] and the same idea as in Chow and Robbins [1, Lemma 1 and 2] we have the following lemma.

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An extension of the hong-park version of the chow-robbins theorem on sums of nonintegrable random variables

  • Adler, Andre;Rosalsky, Andrew
    • Journal of the Korean Mathematical Society
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    • v.32 no.2
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    • pp.363-370
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    • 1995
  • A famous result of Chow and Robbins [8] asserts that if ${X_n, n \geq 1}$ are independent and identically distributed (i.i.d.) random variables with $E$\mid$X_1$\mid$ = \infty$, then for each sequence of constants ${M_n, n \geq 1}$ either $$ (1) lim inf_{n\to\infty} $\mid$\frac{M_n}{\sum_{j=1}^{n}X_j}$\mid$ = 0 almost certainly (a.c.) $$ or $$ (2) lim sup_{n\to\infty}$\mid$\frac{M_n}{\sum_{j=1}^{n}X_j}$\mid$ = \infty a.c. $$ and thus $P{lim_{n\to\infty} \sum_{j=1}^{n}X_j/M_n = 1} = 0$. Note that both (1) and (2) may indeed prevail.

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THE ALMOST SURE CONVERGENCE OF WEIGHTED AVERAGES UNDER NEGATIVE QUADRANT DEPENDENCE

  • Ryu, Dae-Hee
    • Journal of applied mathematics & informatics
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    • v.27 no.3_4
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    • pp.885-893
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    • 2009
  • In this paper we study the strong law of large numbers for weighted average of pairwise negatively quadrant dependent random variables. This result extends that of Jamison et al.(Convergence of weight averages of independent random variables Z. Wahrsch. Verw Gebiete(1965) 4 40-44) to the negative quadrant dependence.

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ON THE WEAK LAW OF LARGE NUMBERS FOR ARRAYS OF PAIRWISE INDEPENDENT RANDOM VARIABLES

  • Hong, Dug-Hun;Hwang, Seok-Yoon;Kwon, Joong-Sung
    • Communications of the Korean Mathematical Society
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    • v.9 no.2
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    • pp.419-421
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    • 1994
  • Recently Hong and Oh [5] provided a fairly general weak law for arrays in the following form: Let {(X/sub ni/, l ≤ i ≤ k/sub n/), n ≥ l}, k/sub n/ → ∞ as n → ∞, be an array of random variables on (Ω, F, P) and set F/sub nj/ = σ{X/sub ni/, 1 ≤ i ≤ j}, 1 ≤ j ≤ k/sub n/, n ≥ 1, and F/sub n0/ = {ø, Ω}, n ≥ 1. Suppose that (equation omitted) aP { X/sub ni/ /sup p/ > a} → 0 as a → ∞ uniformly in n for some 0 < p < 2. Then S/sub n//(equation omitted) → 0 in probability as n → ∞ where S/sub n/ = (equation omitted)(X/sub ni/ - E(X/sib ni/I( X/sub ni/ /sub p/ ≤ k/sub n/) F/sub n,i-l/)). In this note, we will prove the following result under the same domination condition of Hong and Oh [5].(omitted)

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