• Title/Summary/Keyword: negative quadrant dependent 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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Convergence of weighted sums of linearly negative quadrant dependent random variables (선형 음의 사분 종속확률변수에서 가중합에 대한 수렴성 연구)

  • Lee, Seung-Woo;Baek, Jong-Il
    • Journal of Applied Reliability
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    • v.12 no.4
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    • pp.265-274
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    • 2012
  • We in this paper discuss the strong law of large numbers for weighted sums of arrays of rowwise LNQD random variables by using a new exponential inequality of LNQD r.v.'s under suitable conditions and we obtain one of corollary.

STRONG LAW OF LARGE NUMBERS FOR ASYMPTOTICALLY NEGATIVE DEPENDENT RANDOM VARIABLES WITH APPLICATIONS

  • Kim, Hyun-Chull
    • Journal of applied mathematics & informatics
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    • v.29 no.1_2
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    • pp.201-210
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    • 2011
  • In this paper, we obtain the H$\`{a}$jeck-R$\`{e}$nyi type inequality and the strong law of large numbers for asymptotically linear negative quadrant dependent random variables by using this inequality. We also give the strong law of large numbers for the linear process under asymptotically linear negative quadrant dependence assumption.

A NOTE ON THE STRONG LAW OF LARGE NUMBERS FOR WEIGHTED SUMS OF NEGATIVELY DEPENDENT RANDOM VARIABLES

  • Lee, S.W.;Kim, T.S.;Kim, H.C.
    • Communications of the Korean Mathematical Society
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    • v.13 no.4
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    • pp.855-863
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    • 1998
  • Some conditions on the strong law of large numbers for weighted sums of negative quadrant dependent random variables are studied. The almost sure convergence of weighted sums of negatively associated random variables is also established, and then it is utilized to obtain strong laws of large numbers for weighted averages of negatively associated random variables.

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EXPONENTIAL PROBABILITY INEQUALITY FOR LINEARLY NEGATIVE QUADRANT DEPENDENT RANDOM VARIABLES

  • Ko, Mi-Hwa;Choi, Yong-Kab;Choi, Yue-Soon
    • Communications of the Korean Mathematical Society
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    • v.22 no.1
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    • pp.137-143
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    • 2007
  • In this paper, a Berstein-Hoeffding type inequality is established for linearly negative quadrant dependent random variables. A condition is given for almost sure convergence and the associated rate of convergence is specified.

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 Complete Convergence for Weighted Sums of Pairwise Negatively Quadrant Dependent Sequences

  • Ko, Mi-Hwa
    • Communications for Statistical Applications and Methods
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    • v.19 no.2
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    • pp.247-256
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    • 2012
  • In this paper we prove the complete convergence for weighted sums of pairwise negatively quadrant dependent random variables. Some results on identically distributed and negatively associated setting of Liang and Su (1999) are generalized and extended to the pairwise negative quadrant dependence case.

On Convergence of Weighted Sums of LNQD Random

  • Kim, So-Youn;Baek, Jong-Il
    • Communications for Statistical Applications and Methods
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    • v.19 no.5
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    • pp.647-654
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    • 2012
  • We discuss the strong convergence for weighted sums of linearly negative quadrant dependent(LNQD) random variables under suitable conditions and the central limit theorem for weighted sums of an LNQD case is also considered. In addition, we derive some corollaries in LNQD setting.